Rak jelita grubego
Rokowania, prognozy i postęp choroby

Rak jelita grubego charakteryzuje się zróżnicowanym rokowaniem, które w dużej mierze zależy od stadium zaawansowania nowotworu, lokalizacji guza pierwotnego oraz obecności określonych markerów biologicznych i genetycznych. Stadium choroby pozostaje kluczowym czynnikiem prognostycznym, z 5-letnimi wskaźnikami przeżycia wahającymi się od 90% do 10%. Lokalizacja guza wpływa na ryzyko nawrotu i śmiertelności, przy czym wczesne stadium raka okrężnicy wiąże się z lepszymi wskaźnikami przeżycia niż rak odbytnicy. Istotne znaczenie mają także markery takie jak poziom CEA, niestabilność mikrosatelitarna (MSI), mutacje KRAS i BRAF oraz ekspresja NAT1, której niska wartość koreluje z gorszym przeżyciem całkowitym (p=0,00046), przeżyciem bez choroby (p=0,00075) i bez progresji (p=0,0013). Dodatkowo, obecność inwazji naczyniowej, stopień zróżnicowania histologicznego oraz typ histologiczny (np. śluzowy gruczolakorak) wpływają negatywnie na rokowanie.

  1. Prognostyczne czynniki dla raka jelita grubego
    1. Stadium zaawansowania jako kluczowy czynnik prognostyczny
    2. Lokalizacja guza a rokowanie
    3. Markery biologiczne i genetyczne
    4. Inne czynniki histopatologiczne
  2. Modele predykcyjne dla raka jelita grubego
    1. Nomogramy w przewidywaniu przeżycia
    2. Modele oparte na uczeniu maszynowym
    3. Modele oparte na stanie odżywienia i zapalnym
  3. Interpretacja wskaźników przeżycia
  4. Znaczenie czynników prognostycznych w podejmowaniu decyzji klinicznych
    1. Znaczenie dla terapii celowanej i immunoterapii
  5. Wnioski końcowe
    1. Kolejne rozdziały

Prognostyczne czynniki dla raka jelita grubego

Rak jelita grubego to jeden z najczęściej występujących nowotworów złośliwych na świecie, charakteryzujący się wysokim wskaźnikiem śmiertelności. 1 Przewidywanie rokowania u pacjentów z rakiem jelita grubego ma kluczowe znaczenie dla podejmowania decyzji klinicznych dotyczących leczenia uzupełniającego oraz dostarczania pacjentom i ich lekarzom precyzyjnych informacji prognostycznych. 2 Wczesne wykrycie i prawidłowe przewidywanie rokowania może pomóc lekarzom w podejmowaniu właściwych decyzji klinicznych i poprawie rokowania pacjentów. 3

Stadium zaawansowania jako kluczowy czynnik prognostyczny

Stadium zaawansowania nowotworu jest najważniejszym czynnikiem prognostycznym w raku jelita grubego. Im niższe stadium przy rozpoznaniu, tym lepsze rokowanie. 4 Guzy ograniczone wyłącznie do okrężnicy lub odbytnicy mają lepsze rokowanie niż te, które przeniknęły przez ścianę jelita grubego lub odbytnicy, bądź rozprzestrzeniły się do innych narządów (przerzuty odległe). 5

Rokowanie pacjentów z rakiem jelita grubego wykazuje znaczną zmienność, przy czym 5-letnie wskaźniki przeżycia wahają się od 90% do 10%, w zależności od stadium choroby i innych istotnych czynników. 6 Stadium choroby wpływa również na wskaźnik czasowy zgonu po nawrocie (TR=1,223; 95% CI 1,067-1,613), ponieważ bardziej zaawansowane stadium było znacząco związane z wyższym ryzykiem zgonu po nawrocie. 7

Lokalizacja guza a rokowanie

Lokalizacja guza pierwotnego jest istotnym czynnikiem prognostycznym. Badania wykazały, że pacjenci z wczesnym stadium raka okrężnicy wykazują wyższy wskaźnik czasowy dla nawrotu (TR=1,712; 95% CI 1,489-2,197), zgonu bez nawrotu (TR=1,933; 95% CI 1,480-2,510) i zgonu po nawrocie (TR=1,847; 95% CI 1,147-2,178) w porównaniu do pacjentów z wczesnym stadium raka odbytnicy. 8 Oznacza to, że pacjenci z wczesnym stadium raka okrężnicy wykazują lepsze wskaźniki przeżycia dla nawrotu choroby, śmiertelności bez nawrotu i śmiertelności po nawrocie w porównaniu do pacjentów w innych stadiach. 9

Dodatkowo, wyniki badań pokazują, że nowotwory we wczesnym stadium okrężnicy mają lepsze rokowanie w zakresie przeżycia swoistego dla nowotworu w porównaniu z nowotworami o późnym początku. 10

Markery biologiczne i genetyczne

Istnieje szereg markerów biologicznych i genetycznych, które mają istotny wpływ na rokowanie w raku jelita grubego:

  • CEA (antygen karcinoembrionalny) – niższy poziom CEA przed operacją wiąże się z lepszym rokowaniem. 11 Wyższy poziom CEA jest związany z gorszym rokowaniem, co potwierdzono w analizach wieloczynnikowych. 12
  • Niestabilność mikrosatelitarna (MSI) – guzy z wysoką MSI mają lepsze rokowanie niż guzy z niską MSI (nazywane guzami stabilnymi mikrosatelitarnie lub MSS). 13
  • Mutacje genów KRAS i BRAF – pacjenci z komórkami raka jelita grubego, które mają mutację genu KRAS, mają gorsze rokowanie, ponieważ leki ukierunkowane molekularnie nie działają na guz. 14 Podobnie, pacjenci z komórkami nowotworowymi posiadającymi mutację genu BRAF również charakteryzują się gorszym rokowaniem. 15
  • Ekspresja NAT1 – niska ekspresja NAT1 w tkankach nowotworu jelita grubego w porównaniu do sąsiadujących tkanek prawidłowych jest istotnie związana z gorszym rokowaniem pacjentów. Analiza przeżycia Kaplana-Meiera wykazała istotny związek między zmniejszoną ekspresją NAT1 a gorszymi wynikami u pacjentów z rakiem jelita grubego, o czym świadczy gorsze przeżycie całkowite (P=0,00046), przeżycie bez choroby (P=0,00075) i przeżycie bez progresji (P=0,0013). 16

Inne czynniki histopatologiczne

Rokowanie jest lepsze, jeśli w tkance usuniętej wraz z guzem nie ma komórek nowotworowych, niż gdy są obecne komórki nowotworowe (tzw. dodatnie marginesy chirurgiczne). 17 Guzy, które nie wykazują inwazji naczyń limfatycznych i krwionośnych, mają lepsze rokowanie niż guzy z inwazją naczyniową. 18

Dodatkowe czynniki histopatologiczne wpływające na rokowanie obejmują:

  • Stopień zróżnicowania – nowotwory o wysokim stopniu złośliwości mają gorsze rokowanie niż nowotwory o niskim stopniu złośliwości. 19
  • Typ histologiczny – śluzowy gruczolakorak, rak z komórkami sygnetowatymi i drobnokomórkowy rak mają gorsze rokowanie niż inne typy guzów jelita grubego. 20
  • Powikłania przy diagnozie – osoby, u których w momencie rozpoznania występuje niedrożność jelit lub perforacja, mają gorsze rokowanie. 21

Modele predykcyjne dla raka jelita grubego

Ze względu na złożoność czynników wpływających na rokowanie opracowano różne modele predykcyjne, które łączą wiele zmiennych w celu dokładniejszego przewidywania przebiegu choroby i przeżycia pacjentów.

Nomogramy w przewidywaniu przeżycia

Nomogramy dla raka jelita grubego to narzędzia predykcyjne zaprojektowane, aby pomóc lekarzom i pacjentom w podejmowaniu decyzji dotyczących leczenia i długoterminowej opieki. 22 Mogą być również wykorzystywane przez badaczy do projektowania i oceny badań klinicznych. 23

Nomogram prawdopodobieństwa przeżycia bez choroby może być stosowany do przewidywania prawdopodobieństwa, że pacjent będzie wolny od raka jelita grubego przez pięć do dziesięciu lat po całkowitej resekcji (chirurgicznym usunięciu wszystkich tkanek nowotworowych). 24 To narzędzie opiera się na bazie danych 1320 pacjentów z niemetastatycznym rakiem jelita grubego leczonych w Memorial Sloan Kettering Cancer Center i zapewnia dokładniejszy obraz 5- lub 10-letniego ryzyka nawrotu niż starsze narzędzia oceny, takie jak system klasyfikacji American Joint Committee on Cancer. 25

Nomogram dla raka jelita grubego może być również stosowany do przewidywania prawdopodobieństwa przeżycia co najmniej pięciu lat po całkowitej resekcji (chirurgicznym usunięciu) wszystkich tkanek nowotworowych. 26 Ten nomogram zapewnia dokładniejszy obraz ogólnego przeżycia 5-letniego niż system klasyfikacji American Joint Committee on Cancer. 27

W przypadku raka jelita grubego wyniki z narzędzia do przewidywania prawdopodobieństwa całkowitego przeżycia opierają się na danych od 128 853 pacjentów z pierwotnym rakiem jelita grubego, zgłoszonych do programu Surveillance, Epidemiology, and End Results (SEER) Narodowego Instytutu Raka, który zbiera dane o przypadkach nowotworów z różnych lokalizacji i źródeł w Stanach Zjednoczonych. 28

Modele oparte na uczeniu maszynowym

Rozwój technologii umożliwił stworzenie bardziej zaawansowanych modeli predykcyjnych opartych na uczeniu maszynowym i analizach wieloczynnikowych. Czynniki transkrypcyjne mogą być wykorzystywane do konstruowania sygnatur prognostycznych raka jelita grubego o silnej mocy predykcyjnej. 29 Model predykcyjny oparty na pięciu czynnikach transkrypcyjnych pomaga zrozumieć ukrytą relację między przeżywalnością pacjentów z rakiem jelita grubego a aktywnością czynników transkrypcyjnych. 30

Moc predykcyjna tego modelu została zweryfikowana na setkach próbek pacjentów z rakiem jelita grubego dostępnych w bazie danych GEO. 31 Wyniki wykazały, że model ma dobrą zdolność przewidywania ogólnego przeżycia w raku jelita grubego. 32

Opracowano również nowy model prognostyczny oparty na długich niekodujących RNA związanych z disulfidptozą, który pomaga lekarzom przewidywać przeżycie różnych pacjentów z rakiem jelita grubego i stosować różne terapie celowane i immunoterapie w zależności od stanu pacjenta. 33 Krzywe przeżycia całkowitego wykazały, że we wszystkich trzech kohortach grupa niskiego ryzyka miała znacznie lepsze rokowanie niż grupa wysokiego ryzyka. 34

Do walidacji zdolności prognostycznych skonstruowanego modelu przeprowadzono analizę regresji Coxa. 35 Różne analizy regresji wykazały, że ocena ryzyka oparta na modelu była niezależnym czynnikiem ryzyka, z współczynnikami ryzyka odpowiednio 1,312 (1,208-1,425) i 1,267 (1,163-1,380). 36 Krzywa ROC wykazała, że ocena ryzyka była najlepszym predyktorem rokowania wśród wszystkich elementów. 37

Modele oparte na stanie odżywienia i zapalnym

Stan odżywienia i zapalny pacjentów z rakiem jelita grubego również może służyć jako czynnik prognostyczny. W badaniu oceniającym wpływ miar odżywienia i stanu zapalnego (wskaźnik kontroli stanu odżywienia (CONUT), prognostyczny wskaźnik odżywczy (PNI) i zmodyfikowany Glasgow Prognostic Score (mGPS)) na całkowite przeżycie (OS) pacjentów z rakiem jelita grubego w IV stadium, wszystkie trzy miary okazały się niezależnymi czynnikami prognostycznymi dla OS po dostosowaniu do znanych czynników (wiek, płeć, BMI, stan sprawności ECOG, lokalizacja guza pierwotnego, poziomy CEA, typ histologiczny, kategoria M i wcześniejsze leczenie chirurgiczne). 38

W analizie jednoczynnikowej wskaźnik CONUT (p<0.001), PNI (p<0.001) i mGPS (p<0.001), a także płeć (p=0.028), BMI (p=0.008), stan sprawności ECOG (p<0.001), lokalizacja guza pierwotnego (p<0.001), poziomy CEA (p<0.001), typ histologiczny (p<0.001), kategoria M (p<0.001) i leczenie chirurgiczne (p<0.001) były związane z rokowaniem. 39 Wszystkie trzy miary okazały się niezależnymi czynnikami prognostycznymi dla OS u pacjentów z rakiem jelita grubego w IV stadium (wskaźnik CONUT, p<0.001; PNI, p<0.001; mGPS, p<0.001). 40

Interpretacja wskaźników przeżycia

Przy interpretacji wskaźników przeżycia w raku jelita grubego należy pamiętać o kilku ważnych kwestiach:

  • Wskaźniki przeżycia mogą dać wyobrażenie o tym, jaki odsetek osób z tym samym typem i stadium nowotworu żyje przez określony czas (zwykle 5 lat) po zdiagnozowaniu. 41
  • Wskaźniki przeżycia są szacunkami i często opierają się na wcześniejszych wynikach dużej liczby osób, które miały określony nowotwór, ale nie mogą przewidzieć, co stanie się w konkretnym przypadku danej osoby. 42
  • Względny wskaźnik przeżycia porównuje osoby z tym samym typem i stadium nowotworu do osób w ogólnej populacji. 43
  • Baza danych SEER śledzi 5-letnie względne wskaźniki przeżycia dla raka okrężnicy i odbytnicy w Stanach Zjednoczonych, w oparciu o to, jak daleko rozprzestrzenił się nowotwór. 44
  • Te liczby odnoszą się tylko do stadium nowotworu w momencie pierwszej diagnozy. Nie mają zastosowania później, jeśli nowotwór rośnie, rozprzestrzenia się lub powraca po leczeniu. 45

Wskaźniki przeżycia są grupowane na podstawie tego, jak daleko rozprzestrzenił się nowotwór, ale również wiek i ogólny stan zdrowia, czy nowotwór rozpoczął się po lewej czy prawej stronie okrężnicy, czy komórki nowotworowe mają określone zmiany genetyczne lub białkowe, jak dobrze nowotwór reaguje na leczenie i inne czynniki również mogą wpływać na rokowanie. 46

Osoby obecnie diagnozowane z rakiem okrężnicy lub odbytnicy mogą mieć lepsze rokowanie niż pokazują te liczby. Metody leczenia ulegają poprawie z czasem, a te liczby są oparte na osobach, które zostały zdiagnozowane i leczone co najmniej 5 lat wcześniej. 47

Znaczenie czynników prognostycznych w podejmowaniu decyzji klinicznych

Walidacja indywidualnych czynników ryzyka, a tym bardziej wielozmiennych modeli predykcyjnych wielu czynników ryzyka dla przerzutów miejscowych, regionalnych lub odległych oraz nawrotu, jest niezwykle ważna, ponieważ mogą one kierować postępowaniem z guzem pierwotnym i dostarczać informacji prognostycznych pacjentom i ich lekarzom onkologom. 48

W badaniu przeprowadzającym pogłębioną ocenę i porównanie 51 czynników ryzyka i 24 modeli predykcyjnych, wyniki sugerują, że mniejszość wpływowych czynników ryzyka jest wykorzystywana w modelach predykcyjnych, co wskazuje na potrzebę bardziej rygorystycznego i systematycznego procesu konstruowania modeli przy użyciu metod opartych na dowodach. 49

Według wcześniej zdefiniowanych kryteriów oceny wiarygodności dowodów, tylko jeden czynnik ryzyka został sklasyfikowany jako przekonujący (inwazja naczyniowa dla LNM w pT1 CRC), odzwierciedlając silną istotność statystyczną i brak oznak stronniczości. 50 Dwanaście (35%) z 34 badanych czynników ryzyka przerzutów miało wielkość efektu sugerującą 3-krotną zmianę w szansach wyniku z p≤0,05. 51 W odniesieniu do 17 badanych czynników ryzyka nawrotu raka jelita grubego, cztery (24%) miały wielkość efektu sugerującą 3-krotną zmianę w szansach wyniku z p≤0,05. Żaden z nich nie przedstawiał przekonujących dowodów. 52

Wyniki sugerują, że wysiłki zmierzające do usunięcia ograniczeń dostępnych dowodów mogłyby być korzystne. Potrzebne są duże prospektywne badania w celu wygenerowania dowodów mniej podatnych na błędy i umożliwiających lepsze budowanie i walidację modeli predykcyjnych. 53

Znaczenie dla terapii celowanej i immunoterapii

Model predykcyjny oparty na pięciu czynnikach transkrypcyjnych i jego funkcje biologiczne dostarczają więcej informacji na temat precyzyjnego leczenia raka jelita grubego, co prowadzi do dalszych badań nad tymi pięcioma genami TF i ich rolą podczas rozwoju raka jelita grubego na poziomie molekularnym. 54

Badania pokazały również istotne znaczenie biomarkerów dla przewidywania odpowiedzi na chemioterapię. Niska ekspresja NAT1 w komórkach raka jelita grubego zwiększa oporność na wiele leków chemioterapeutycznych, w tym winblastynę, docetaksel, gemcytabinę, winkrystynę i daporinad. 55 Co ważne, nadekspresja NAT1 w tych komórkach przywracała wrażliwość na wszystkie pięć leków, dostarczając silnych dowodów, że niedobór NAT1 jest kluczowym czynnikiem napędzającym oporność na te środki terapeutyczne w raku jelita grubego. 56

Obserwacje te sugerują, że obniżona ekspresja NAT1 zwiększa oporność na chemioterapię poprzez promowanie tworzenia komórek macierzystych nowotworów LGR5+. 57 Wyniki wskazują, że obniżona ekspresja NAT1, która przesuwa metabolizm komórkowy w kierunku glikolizy, prawdopodobnie napędza rozwój komórek macierzystych nowotworów LGR5+ i ich chemiooporność. 58

Badania pokazują również, że tłumienie ekspresji NAT1 zwiększa ekspresję VEGFA w komórkach raka jelita grubego. Wzmacnia to sygnalizację VEGFA-VEGFR między komórkami nowotworowymi a komórkami śródbłonka, promując angiogenezę poprzez aktywację komórek śródbłonka. 59 Analiza z wykorzystaniem bazy danych TIMER2.0 pokazuje, że obniżona ekspresja NAT1 jest powiązana z niższą infiltracją tych komórek, co może zmniejszyć efekt terapeutyczny terapii anty-PD-1. 60

Wnioski końcowe

Rokowanie w raku jelita grubego zależy od wielu czynników, w tym stadium zaawansowania nowotworu, lokalizacji guza, cech histopatologicznych, markerów genetycznych i molekularnych, stanu odżywienia i zapalnego pacjenta. Modele predykcyjne łączące te różne czynniki pozwalają na dokładniejsze przewidywanie przebiegu choroby i przeżycia pacjentów.

Walidacja czynników ryzyka i opracowanie wielozmiennych modeli predykcyjnych są niezwykle ważne, ponieważ mogą kierować postępowaniem z guzem pierwotnym i dostarczać informacji prognostycznych pacjentom i ich lekarzom onkologom. Identyfikacja biomarkerów prognostycznych ma szczególne znaczenie dla przewidywania całkowitego lub wolnego od progresji przeżycia lub wskaźników nawrotu, informowania pacjentów i wspierania właściwego podejmowania decyzji medycznych.

Ciągły rozwój technologii i metodologii badawczych umożliwia tworzenie coraz bardziej precyzyjnych modeli predykcyjnych, które mogą być wykorzystywane do indywidualizacji leczenia i poprawy wyników terapeutycznych u pacjentów z rakiem jelita grubego.

Kolejne rozdziały

Zapraszamy do dalszego czytania naszego leksykonu.

Wybierz kolejny rozdział z menu poniżej, aby otworzyć nową podstronę kompedium wiedzy i uzyskać szczegółowe informację o leku, substancji lub chorobie.

  1. 09.04.2026
  2. www.leksykon.com.pl

Materiały źródłowe

  • #1 A disulfidptosis-related lncRNA index predicting prognosis and the tumor microenvironment in colorectal cancer | Scientific Reports
    https://www.nature.com/articles/s41598-023-47472-3
    Colorectal cancer (CRC) is a common and deadly cancer worldwide with a high lethality rate. […] The purpose of this study was to explore the relationship between disulfidptosis-related lncRNAs (DRLs) and CRC and to develop a prognostic model for CRC and DRLs. […] In summary, we developed a prognostic marker consisting of lncRNAs associated with disulfidptosis to help clinicians predict the survival of different CRC patients and use different targeted therapies and immunotherapies depending on the condition. […] Early detection and correct prediction of prognosis can help physicians make correct clinical decisions and improve patient prognosis. […] Therefore, the search for biomarkers with prognostic significance is particularly important for predicting overall or progression-free survival or recurrence rates, informing patients, and supporting proper medical decision-making.
  • #2 Risk factors and risk prediction models for colorectal cancer metastasis and recurrence: an umbrella review of systematic reviews and meta-analyses of observational studies
    https://pmc.ncbi.nlm.nih.gov/articles/PMC7318747/
    There is a clear need for systematic appraisal of models/factors predicting colorectal cancer (CRC) metastasis and recurrence because clinical decisions about adjuvant treatment are taken on the basis of such variables. […] Validating individual risk factors and even more so multivariable prediction models of multiple risk factors for local, regional, or distant metastasis and recurrence is crucially important as these could guide management of the primary tumor and provide prognostic information for patients and their cancer clinicians. […] This study provides an in-depth evaluation and cross-assessment of 51 risk factors and 24 prediction models. Our findings suggest that a minority of influential risk factors are employed in prediction models, which indicates the need for a more rigorous and systematic model construction process following evidence-based methods.
  • #3 A disulfidptosis-related lncRNA index predicting prognosis and the tumor microenvironment in colorectal cancer | Scientific Reports
    https://www.nature.com/articles/s41598-023-47472-3
    Colorectal cancer (CRC) is a common and deadly cancer worldwide with a high lethality rate. […] The purpose of this study was to explore the relationship between disulfidptosis-related lncRNAs (DRLs) and CRC and to develop a prognostic model for CRC and DRLs. […] In summary, we developed a prognostic marker consisting of lncRNAs associated with disulfidptosis to help clinicians predict the survival of different CRC patients and use different targeted therapies and immunotherapies depending on the condition. […] Early detection and correct prediction of prognosis can help physicians make correct clinical decisions and improve patient prognosis. […] Therefore, the search for biomarkers with prognostic significance is particularly important for predicting overall or progression-free survival or recurrence rates, informing patients, and supporting proper medical decision-making.
  • #4 Prognosis and survival for colorectal cancer | Canadian Cancer Society
    https://cancer.ca/en/cancer-information/cancer-types/colorectal/prognosis-and-survival
    If you have colorectal cancer, you may have questions about your prognosis. A prognosis is the doctors best estimate of how cancer will affect someone and how it will respond to treatment. Prognosis and survival depend on many factors. Only a doctor familiar with your medical history, the type and stage and other features of the cancer, the treatments chosen and the response to treatment can put all of this information together with survival statistics to arrive at a prognosis. […] Stage is the most important prognostic factor for colorectal cancer. The lower the stage at diagnosis, the better the outcome. Tumours that are only in the colon or rectum have a better prognosis than those that have grown through the wall of the colon or rectum, or have spread to other organs (called distant metastases).
  • #5 Prognosis and survival for colorectal cancer | Canadian Cancer Society
    https://cancer.ca/en/cancer-information/cancer-types/colorectal/prognosis-and-survival
    If you have colorectal cancer, you may have questions about your prognosis. A prognosis is the doctors best estimate of how cancer will affect someone and how it will respond to treatment. Prognosis and survival depend on many factors. Only a doctor familiar with your medical history, the type and stage and other features of the cancer, the treatments chosen and the response to treatment can put all of this information together with survival statistics to arrive at a prognosis. […] Stage is the most important prognostic factor for colorectal cancer. The lower the stage at diagnosis, the better the outcome. Tumours that are only in the colon or rectum have a better prognosis than those that have grown through the wall of the colon or rectum, or have spread to other organs (called distant metastases).
  • #6 Exploring the impact of stage and tumor site on colorectal cancer survival: Bayesian survival modeling | Scientific Reports
    https://www.nature.com/articles/s41598-024-54943-8
    Colorectal cancer is a prevalent malignancy with global significance. This retrospective study aimed to investigate the influence of stage and tumor site on survival outcomes in 284 colorectal cancer patients diagnosed between 2001 and 2017. […] Results demonstrated significantly higher time ratios for disease recurrence (TR=1.712, 95% CI 1.4892.197), mortality without recurrence (TR=1.933, 1.4802.510), and mortality after recurrence (TR=1.847, 1.1472.178) in early-stage colon cancer compared to early-stage rectal cancer. […] Early-stage colon cancer demonstrated improved survival rates for disease recurrence, mortality without recurrence, and mortality after recurrence compared to other stages. […] The prognosis of CRC patients exhibits substantial variability, with 5-year survival rates ranging from 90 to 10%, contingent upon the stage of the disease and other pertinent factors.
  • #7 Exploring the impact of stage and tumor site on colorectal cancer survival: Bayesian survival modeling | Scientific Reports
    https://www.nature.com/articles/s41598-024-54943-8
    The disease stage also influenced the time ratio of death after relapse (TR=1.223; 95% CI 1.0671.613), as a more advanced stage was significantly associated with higher rates of death after recurrence but did not exhibit a significant effect on recurrence and death without recurrence. […] When patients with Early_RC were compared to Early_CC, patients with early-stage colon cancer exhibited a higher time ratio for recurrence (TR=1.712; 95% CI 1.4892.197), death without recurrence (TR=1.933; 95% CI 1.4802.510), and death after recurrence (TR=1.847; 95% CI 1.1472.178). […] The findings highlight the significant influence of both stage and tumor sites on survival outcomes. Specifically, patients with early-stage colon cancer exhibited higher rates of survival for disease recurrence, mortality without recurrence, and mortality after recurrence compared to patients in other stages.
  • #8 Exploring the impact of stage and tumor site on colorectal cancer survival: Bayesian survival modeling | Scientific Reports
    https://www.nature.com/articles/s41598-024-54943-8
    The disease stage also influenced the time ratio of death after relapse (TR=1.223; 95% CI 1.0671.613), as a more advanced stage was significantly associated with higher rates of death after recurrence but did not exhibit a significant effect on recurrence and death without recurrence. […] When patients with Early_RC were compared to Early_CC, patients with early-stage colon cancer exhibited a higher time ratio for recurrence (TR=1.712; 95% CI 1.4892.197), death without recurrence (TR=1.933; 95% CI 1.4802.510), and death after recurrence (TR=1.847; 95% CI 1.1472.178). […] The findings highlight the significant influence of both stage and tumor sites on survival outcomes. Specifically, patients with early-stage colon cancer exhibited higher rates of survival for disease recurrence, mortality without recurrence, and mortality after recurrence compared to patients in other stages.
  • #9 Exploring the impact of stage and tumor site on colorectal cancer survival: Bayesian survival modeling | Scientific Reports
    https://www.nature.com/articles/s41598-024-54943-8
    The disease stage also influenced the time ratio of death after relapse (TR=1.223; 95% CI 1.0671.613), as a more advanced stage was significantly associated with higher rates of death after recurrence but did not exhibit a significant effect on recurrence and death without recurrence. […] When patients with Early_RC were compared to Early_CC, patients with early-stage colon cancer exhibited a higher time ratio for recurrence (TR=1.712; 95% CI 1.4892.197), death without recurrence (TR=1.933; 95% CI 1.4802.510), and death after recurrence (TR=1.847; 95% CI 1.1472.178). […] The findings highlight the significant influence of both stage and tumor sites on survival outcomes. Specifically, patients with early-stage colon cancer exhibited higher rates of survival for disease recurrence, mortality without recurrence, and mortality after recurrence compared to patients in other stages.
  • #10
    https://link.springer.com/article/10.1007/s00384-023-04543-1
    To predict cancer-specific survival, a refined nomogram model and brand-new risk-stratifying system were established to classify the risk levels of patients with early-onset locally advanced colon cancer (LACC). […] Early-onset colon cancers had poorer prognosis (T4, N2, TNM stage III, CEA, tumor deposit, and nerve invasion), and a higher proportion received radiotherapy and systemic therapy (P0.001). In the survival analysis, cancer-specific survival (CSS) was better in patients with early-onset LACC than in those with late-onset LACC (P 0.001). […] We developed a novel nomogram model to predict CSS in patients with early-onset LACC it provided a reference in prognosis prediction and selection of individualized treatment, helping clinicians in decision-making.
  • #11 Prognosis and survival for colorectal cancer | Canadian Cancer Society
    https://cancer.ca/en/cancer-information/cancer-types/colorectal/prognosis-and-survival
    The prognosis is better if there are no cancer cells in the tissue removed with the tumour than if there are cancer cells in the tissue (called positive surgical margins). […] Tumours that dont have lymphovascular invasion have a better prognosis than tumours that have lymphovascular invasion. […] The lower the CEA level before surgery, the better the prognosis. […] People who have a bowel obstruction or perforation at the time of diagnosis have a poorer prognosis. […] High-grade cancers have a poorer prognosis than low-grade cancers. […] Mucinous adenocarcinoma, signet ring cell carcinoma and small cell carcinoma have a poorer prognosis than other types of colorectal tumours. […] Tumours that have cells with high MSI have a better prognosis than tumours with low MSI (called microsatellite stable or MSS tumours). […] People with colorectal cancer cells that have the KRAS gene mutation have a poorer prognosis because targeted therapy drugs will not work on the tumour. […] As a result, people with cancer cells that have the BRAF gene mutation have a poorer prognosis.
  • #12 Nutritional and inflammatory measures predict survival of patients with stage IV colorectal cancer | BMC Cancer | Full Text
    https://bmccancer.biomedcentral.com/articles/10.1186/s12885-020-07560-3
    In univariate analysis, CONUT score (p0.001), PNI (p0.001), and mGPS (p0.001), as well as gender (p=0.028), BMI (p=0.008), ECOG performance status (p0.001), location of primary tumor (p0.001), CEA levels (p0.001), histological type (p0.001), M category (p0.001), and surgical treatment (p0.001), were associated with prognosis. […] Multivariate analyses were performed, adjusting for clinical factors that were significant in univariate analyses (gender, BMI, ECOG performance status, location of primary tumor, CEA levels, histological type, M category, and surgical treatment); age was also included given the prior knowledge according to TNM eighth edition. All three measures were found to be independent prognostic factors for OS in patients with stage IV CRC (CONUT score, p0.001; PNI, p0.001; mGPS, p0.001). […] The present study revealed that CONUT score, PNI, and mGPS, which consist of these factors, are strongly correlated with prognosis in stage IV CRC patients.
  • #13 Prognosis and survival for colorectal cancer | Canadian Cancer Society
    https://cancer.ca/en/cancer-information/cancer-types/colorectal/prognosis-and-survival
    The prognosis is better if there are no cancer cells in the tissue removed with the tumour than if there are cancer cells in the tissue (called positive surgical margins). […] Tumours that dont have lymphovascular invasion have a better prognosis than tumours that have lymphovascular invasion. […] The lower the CEA level before surgery, the better the prognosis. […] People who have a bowel obstruction or perforation at the time of diagnosis have a poorer prognosis. […] High-grade cancers have a poorer prognosis than low-grade cancers. […] Mucinous adenocarcinoma, signet ring cell carcinoma and small cell carcinoma have a poorer prognosis than other types of colorectal tumours. […] Tumours that have cells with high MSI have a better prognosis than tumours with low MSI (called microsatellite stable or MSS tumours). […] People with colorectal cancer cells that have the KRAS gene mutation have a poorer prognosis because targeted therapy drugs will not work on the tumour. […] As a result, people with cancer cells that have the BRAF gene mutation have a poorer prognosis.
  • #14 Prognosis and survival for colorectal cancer | Canadian Cancer Society
    https://cancer.ca/en/cancer-information/cancer-types/colorectal/prognosis-and-survival
    The prognosis is better if there are no cancer cells in the tissue removed with the tumour than if there are cancer cells in the tissue (called positive surgical margins). […] Tumours that dont have lymphovascular invasion have a better prognosis than tumours that have lymphovascular invasion. […] The lower the CEA level before surgery, the better the prognosis. […] People who have a bowel obstruction or perforation at the time of diagnosis have a poorer prognosis. […] High-grade cancers have a poorer prognosis than low-grade cancers. […] Mucinous adenocarcinoma, signet ring cell carcinoma and small cell carcinoma have a poorer prognosis than other types of colorectal tumours. […] Tumours that have cells with high MSI have a better prognosis than tumours with low MSI (called microsatellite stable or MSS tumours). […] People with colorectal cancer cells that have the KRAS gene mutation have a poorer prognosis because targeted therapy drugs will not work on the tumour. […] As a result, people with cancer cells that have the BRAF gene mutation have a poorer prognosis.
  • #15 Prognosis and survival for colorectal cancer | Canadian Cancer Society
    https://cancer.ca/en/cancer-information/cancer-types/colorectal/prognosis-and-survival
    The prognosis is better if there are no cancer cells in the tissue removed with the tumour than if there are cancer cells in the tissue (called positive surgical margins). […] Tumours that dont have lymphovascular invasion have a better prognosis than tumours that have lymphovascular invasion. […] The lower the CEA level before surgery, the better the prognosis. […] People who have a bowel obstruction or perforation at the time of diagnosis have a poorer prognosis. […] High-grade cancers have a poorer prognosis than low-grade cancers. […] Mucinous adenocarcinoma, signet ring cell carcinoma and small cell carcinoma have a poorer prognosis than other types of colorectal tumours. […] Tumours that have cells with high MSI have a better prognosis than tumours with low MSI (called microsatellite stable or MSS tumours). […] People with colorectal cancer cells that have the KRAS gene mutation have a poorer prognosis because targeted therapy drugs will not work on the tumour. […] As a result, people with cancer cells that have the BRAF gene mutation have a poorer prognosis.
  • #16
    https://link.springer.com/article/10.1186/s13148-025-01882-4
    Low NAT1 expression in CRC tumor tissues, relative to adjacent normal tissues, is significantly associated with a poorer patient prognosis. […] The Kaplan-Meier survival analysis revealed a significant association between reduced NAT1 expression and poorer outcomes in CRC patients, as evidenced by worse overall survival (P=0.00046), disease-free survival (P=0.00075), and progression-free survival (P=0.0013). […] Low NAT1 expression is associated with decreased responsiveness to chemotherapies in breast cancer patients. […] In this study, we demonstrated that NAT1 deficiency in colorectal cancer (CRC) cells increases resistance to multiple chemotherapeutic agents, including vinblastine, docetaxel, gemcitabine, vincristine, and daporinad. […] Importantly, overexpression of NAT1 in these cells restored sensitivity to all five drugs, providing strong evidence that NAT1 deficiency is a key factor driving resistance to these therapeutic agents in CRC.
  • #17 Prognosis and survival for colorectal cancer | Canadian Cancer Society
    https://cancer.ca/en/cancer-information/cancer-types/colorectal/prognosis-and-survival
    The prognosis is better if there are no cancer cells in the tissue removed with the tumour than if there are cancer cells in the tissue (called positive surgical margins). […] Tumours that dont have lymphovascular invasion have a better prognosis than tumours that have lymphovascular invasion. […] The lower the CEA level before surgery, the better the prognosis. […] People who have a bowel obstruction or perforation at the time of diagnosis have a poorer prognosis. […] High-grade cancers have a poorer prognosis than low-grade cancers. […] Mucinous adenocarcinoma, signet ring cell carcinoma and small cell carcinoma have a poorer prognosis than other types of colorectal tumours. […] Tumours that have cells with high MSI have a better prognosis than tumours with low MSI (called microsatellite stable or MSS tumours). […] People with colorectal cancer cells that have the KRAS gene mutation have a poorer prognosis because targeted therapy drugs will not work on the tumour. […] As a result, people with cancer cells that have the BRAF gene mutation have a poorer prognosis.
  • #18 Prognosis and survival for colorectal cancer | Canadian Cancer Society
    https://cancer.ca/en/cancer-information/cancer-types/colorectal/prognosis-and-survival
    The prognosis is better if there are no cancer cells in the tissue removed with the tumour than if there are cancer cells in the tissue (called positive surgical margins). […] Tumours that dont have lymphovascular invasion have a better prognosis than tumours that have lymphovascular invasion. […] The lower the CEA level before surgery, the better the prognosis. […] People who have a bowel obstruction or perforation at the time of diagnosis have a poorer prognosis. […] High-grade cancers have a poorer prognosis than low-grade cancers. […] Mucinous adenocarcinoma, signet ring cell carcinoma and small cell carcinoma have a poorer prognosis than other types of colorectal tumours. […] Tumours that have cells with high MSI have a better prognosis than tumours with low MSI (called microsatellite stable or MSS tumours). […] People with colorectal cancer cells that have the KRAS gene mutation have a poorer prognosis because targeted therapy drugs will not work on the tumour. […] As a result, people with cancer cells that have the BRAF gene mutation have a poorer prognosis.
  • #19 Prognosis and survival for colorectal cancer | Canadian Cancer Society
    https://cancer.ca/en/cancer-information/cancer-types/colorectal/prognosis-and-survival
    The prognosis is better if there are no cancer cells in the tissue removed with the tumour than if there are cancer cells in the tissue (called positive surgical margins). […] Tumours that dont have lymphovascular invasion have a better prognosis than tumours that have lymphovascular invasion. […] The lower the CEA level before surgery, the better the prognosis. […] People who have a bowel obstruction or perforation at the time of diagnosis have a poorer prognosis. […] High-grade cancers have a poorer prognosis than low-grade cancers. […] Mucinous adenocarcinoma, signet ring cell carcinoma and small cell carcinoma have a poorer prognosis than other types of colorectal tumours. […] Tumours that have cells with high MSI have a better prognosis than tumours with low MSI (called microsatellite stable or MSS tumours). […] People with colorectal cancer cells that have the KRAS gene mutation have a poorer prognosis because targeted therapy drugs will not work on the tumour. […] As a result, people with cancer cells that have the BRAF gene mutation have a poorer prognosis.
  • #20 Prognosis and survival for colorectal cancer | Canadian Cancer Society
    https://cancer.ca/en/cancer-information/cancer-types/colorectal/prognosis-and-survival
    The prognosis is better if there are no cancer cells in the tissue removed with the tumour than if there are cancer cells in the tissue (called positive surgical margins). […] Tumours that dont have lymphovascular invasion have a better prognosis than tumours that have lymphovascular invasion. […] The lower the CEA level before surgery, the better the prognosis. […] People who have a bowel obstruction or perforation at the time of diagnosis have a poorer prognosis. […] High-grade cancers have a poorer prognosis than low-grade cancers. […] Mucinous adenocarcinoma, signet ring cell carcinoma and small cell carcinoma have a poorer prognosis than other types of colorectal tumours. […] Tumours that have cells with high MSI have a better prognosis than tumours with low MSI (called microsatellite stable or MSS tumours). […] People with colorectal cancer cells that have the KRAS gene mutation have a poorer prognosis because targeted therapy drugs will not work on the tumour. […] As a result, people with cancer cells that have the BRAF gene mutation have a poorer prognosis.
  • #21 Prognosis and survival for colorectal cancer | Canadian Cancer Society
    https://cancer.ca/en/cancer-information/cancer-types/colorectal/prognosis-and-survival
    The prognosis is better if there are no cancer cells in the tissue removed with the tumour than if there are cancer cells in the tissue (called positive surgical margins). […] Tumours that dont have lymphovascular invasion have a better prognosis than tumours that have lymphovascular invasion. […] The lower the CEA level before surgery, the better the prognosis. […] People who have a bowel obstruction or perforation at the time of diagnosis have a poorer prognosis. […] High-grade cancers have a poorer prognosis than low-grade cancers. […] Mucinous adenocarcinoma, signet ring cell carcinoma and small cell carcinoma have a poorer prognosis than other types of colorectal tumours. […] Tumours that have cells with high MSI have a better prognosis than tumours with low MSI (called microsatellite stable or MSS tumours). […] People with colorectal cancer cells that have the KRAS gene mutation have a poorer prognosis because targeted therapy drugs will not work on the tumour. […] As a result, people with cancer cells that have the BRAF gene mutation have a poorer prognosis.
  • #22 Colon Cancer Prediction Tools | Memorial Sloan Kettering Cancer Center
    https://www.mskcc.org/cancer-care/types/colon/prediction-tools
    Our colorectal cancer nomograms are online prediction tools that are designed to help physicians and patients make decisions about treatment and long-term follow-up care. […] They may also be used by researchers to help design and evaluate clinical trials. […] Our disease-free probability nomogram can be used to predict the probability that a patient will be disease-free from colon cancer five to ten years following complete resection, or surgical removal of all cancerous tissue. […] This tool is based on a database of 1,320 patients with nonmetastatic colon cancer treated at Memorial Sloan Kettering Cancer Center. It provides a more accurate picture of the five- or ten-year risk of recurrence than older assessment tools, such as the staging system of the American Joint Committee on Cancer.
  • #23 Colon Cancer Prediction Tools | Memorial Sloan Kettering Cancer Center
    https://www.mskcc.org/cancer-care/types/colon/prediction-tools
    Our colorectal cancer nomograms are online prediction tools that are designed to help physicians and patients make decisions about treatment and long-term follow-up care. […] They may also be used by researchers to help design and evaluate clinical trials. […] Our disease-free probability nomogram can be used to predict the probability that a patient will be disease-free from colon cancer five to ten years following complete resection, or surgical removal of all cancerous tissue. […] This tool is based on a database of 1,320 patients with nonmetastatic colon cancer treated at Memorial Sloan Kettering Cancer Center. It provides a more accurate picture of the five- or ten-year risk of recurrence than older assessment tools, such as the staging system of the American Joint Committee on Cancer.
  • #24 Colon Cancer Prediction Tools | Memorial Sloan Kettering Cancer Center
    https://www.mskcc.org/cancer-care/types/colon/prediction-tools
    Our colorectal cancer nomograms are online prediction tools that are designed to help physicians and patients make decisions about treatment and long-term follow-up care. […] They may also be used by researchers to help design and evaluate clinical trials. […] Our disease-free probability nomogram can be used to predict the probability that a patient will be disease-free from colon cancer five to ten years following complete resection, or surgical removal of all cancerous tissue. […] This tool is based on a database of 1,320 patients with nonmetastatic colon cancer treated at Memorial Sloan Kettering Cancer Center. It provides a more accurate picture of the five- or ten-year risk of recurrence than older assessment tools, such as the staging system of the American Joint Committee on Cancer.
  • #25 Colon Cancer Prediction Tools | Memorial Sloan Kettering Cancer Center
    https://www.mskcc.org/cancer-care/types/colon/prediction-tools
    Our colorectal cancer nomograms are online prediction tools that are designed to help physicians and patients make decisions about treatment and long-term follow-up care. […] They may also be used by researchers to help design and evaluate clinical trials. […] Our disease-free probability nomogram can be used to predict the probability that a patient will be disease-free from colon cancer five to ten years following complete resection, or surgical removal of all cancerous tissue. […] This tool is based on a database of 1,320 patients with nonmetastatic colon cancer treated at Memorial Sloan Kettering Cancer Center. It provides a more accurate picture of the five- or ten-year risk of recurrence than older assessment tools, such as the staging system of the American Joint Committee on Cancer.
  • #26 Colon Cancer Prediction Tools | Memorial Sloan Kettering Cancer Center
    https://www.mskcc.org/cancer-care/types/colon/prediction-tools
    This colon cancer nomogram can be used to predict the probability of surviving at least five years following complete resection (surgical removal) of all cancerous tissue. […] This nomogram provides a more accurate picture of overall survival at five years than the American Joint Committee on Cancer staging system.
  • #27 Colon Cancer Prediction Tools | Memorial Sloan Kettering Cancer Center
    https://www.mskcc.org/cancer-care/types/colon/prediction-tools
    This colon cancer nomogram can be used to predict the probability of surviving at least five years following complete resection (surgical removal) of all cancerous tissue. […] This nomogram provides a more accurate picture of overall survival at five years than the American Joint Committee on Cancer staging system.
  • #28 Colorectal Cancer Nomograms | Memorial Sloan Kettering Cancer Center
    https://www.mskcc.org/nomograms/colorectal
    Our colorectal cancer nomograms are prediction tools designed to help patients and their physicians calculate the likely outcomes of their surgical treatment for colon cancer. […] Results from our overall survival probability prediction tool are based on data from 128,853 primary colon cancer patients reported to the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute, which collects data on cancer cases from various locations and sources throughout the United States. […] Our overall survival nomogram is a tool designed to predict the likelihood of surviving at least five years after undergoing a complete resection (surgical removal of all cancerous tissue) for colon cancer. […] By submitting more information, you will get a more accurate overall survival estimate.
  • #29 Transcription factor expression as a predictor of colon cancer prognosis: a machine learning practice | BMC Medical Genomics | Full Text
    https://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-020-00775-0
    Colon cancer is one of the leading causes of cancer deaths in the USA and around the world. […] Overall, our results prove our prediction model has a strong prediction power on colon cancer prognosis. […] Transcription factors can be used to construct colon cancer prognostic signatures with strong prediction power. […] Our five TF-based predictive model would help with understanding the hidden relationship between colon cancer patient survival and transcription factor activities. […] The prediction power of our model is validated on hundreds of colon cancer patient samples available in the GEO database. […] The results showed that our model has a good predicting power in predicting colon cancer overall survival. […] Our predictive model and its biological functions would provide more insights in the precision treatment of colon cancer, which leads to further investigation on these five TF genes and their roles during the development of colon cancer at the molecular level.
  • #30 Transcription factor expression as a predictor of colon cancer prognosis: a machine learning practice | BMC Medical Genomics | Full Text
    https://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-020-00775-0
    Colon cancer is one of the leading causes of cancer deaths in the USA and around the world. […] Overall, our results prove our prediction model has a strong prediction power on colon cancer prognosis. […] Transcription factors can be used to construct colon cancer prognostic signatures with strong prediction power. […] Our five TF-based predictive model would help with understanding the hidden relationship between colon cancer patient survival and transcription factor activities. […] The prediction power of our model is validated on hundreds of colon cancer patient samples available in the GEO database. […] The results showed that our model has a good predicting power in predicting colon cancer overall survival. […] Our predictive model and its biological functions would provide more insights in the precision treatment of colon cancer, which leads to further investigation on these five TF genes and their roles during the development of colon cancer at the molecular level.
  • #31 Transcription factor expression as a predictor of colon cancer prognosis: a machine learning practice | BMC Medical Genomics | Full Text
    https://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-020-00775-0
    Colon cancer is one of the leading causes of cancer deaths in the USA and around the world. […] Overall, our results prove our prediction model has a strong prediction power on colon cancer prognosis. […] Transcription factors can be used to construct colon cancer prognostic signatures with strong prediction power. […] Our five TF-based predictive model would help with understanding the hidden relationship between colon cancer patient survival and transcription factor activities. […] The prediction power of our model is validated on hundreds of colon cancer patient samples available in the GEO database. […] The results showed that our model has a good predicting power in predicting colon cancer overall survival. […] Our predictive model and its biological functions would provide more insights in the precision treatment of colon cancer, which leads to further investigation on these five TF genes and their roles during the development of colon cancer at the molecular level.
  • #32 Transcription factor expression as a predictor of colon cancer prognosis: a machine learning practice | BMC Medical Genomics | Full Text
    https://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-020-00775-0
    Colon cancer is one of the leading causes of cancer deaths in the USA and around the world. […] Overall, our results prove our prediction model has a strong prediction power on colon cancer prognosis. […] Transcription factors can be used to construct colon cancer prognostic signatures with strong prediction power. […] Our five TF-based predictive model would help with understanding the hidden relationship between colon cancer patient survival and transcription factor activities. […] The prediction power of our model is validated on hundreds of colon cancer patient samples available in the GEO database. […] The results showed that our model has a good predicting power in predicting colon cancer overall survival. […] Our predictive model and its biological functions would provide more insights in the precision treatment of colon cancer, which leads to further investigation on these five TF genes and their roles during the development of colon cancer at the molecular level.
  • #33 A disulfidptosis-related lncRNA index predicting prognosis and the tumor microenvironment in colorectal cancer | Scientific Reports
    https://www.nature.com/articles/s41598-023-47472-3
    Colorectal cancer (CRC) is a common and deadly cancer worldwide with a high lethality rate. […] The purpose of this study was to explore the relationship between disulfidptosis-related lncRNAs (DRLs) and CRC and to develop a prognostic model for CRC and DRLs. […] In summary, we developed a prognostic marker consisting of lncRNAs associated with disulfidptosis to help clinicians predict the survival of different CRC patients and use different targeted therapies and immunotherapies depending on the condition. […] Early detection and correct prediction of prognosis can help physicians make correct clinical decisions and improve patient prognosis. […] Therefore, the search for biomarkers with prognostic significance is particularly important for predicting overall or progression-free survival or recurrence rates, informing patients, and supporting proper medical decision-making.
  • #34 A disulfidptosis-related lncRNA index predicting prognosis and the tumor microenvironment in colorectal cancer | Scientific Reports
    https://www.nature.com/articles/s41598-023-47472-3
    Therefore, this study aimed to determine the prognostic role of lncRNAs related to disulfidptosis in colorectal cancer, identify new targets for biological therapies, develop a survival risk prediction model that can be used for prognostic prediction and selection of specific therapies for CRC patients, and uncover the mechanisms of disulfide rupture-induced cell death in colorectal cancer. […] The overall survival curves showed that in all three cohorts, the low-risk group had a significantly better prognosis than the high-risk group. […] To validate the forecasting capabilities of the model we constructed, Cox regression analysis was performed. […] Different regression analyses showed that the model-based calculated risk score was an independent risk factor, with hazard ratios of 1.312 (1.2081.425) and 1.267 (1.1631.380), respectively.
  • #35 A disulfidptosis-related lncRNA index predicting prognosis and the tumor microenvironment in colorectal cancer | Scientific Reports
    https://www.nature.com/articles/s41598-023-47472-3
    Therefore, this study aimed to determine the prognostic role of lncRNAs related to disulfidptosis in colorectal cancer, identify new targets for biological therapies, develop a survival risk prediction model that can be used for prognostic prediction and selection of specific therapies for CRC patients, and uncover the mechanisms of disulfide rupture-induced cell death in colorectal cancer. […] The overall survival curves showed that in all three cohorts, the low-risk group had a significantly better prognosis than the high-risk group. […] To validate the forecasting capabilities of the model we constructed, Cox regression analysis was performed. […] Different regression analyses showed that the model-based calculated risk score was an independent risk factor, with hazard ratios of 1.312 (1.2081.425) and 1.267 (1.1631.380), respectively.
  • #36 A disulfidptosis-related lncRNA index predicting prognosis and the tumor microenvironment in colorectal cancer | Scientific Reports
    https://www.nature.com/articles/s41598-023-47472-3
    Therefore, this study aimed to determine the prognostic role of lncRNAs related to disulfidptosis in colorectal cancer, identify new targets for biological therapies, develop a survival risk prediction model that can be used for prognostic prediction and selection of specific therapies for CRC patients, and uncover the mechanisms of disulfide rupture-induced cell death in colorectal cancer. […] The overall survival curves showed that in all three cohorts, the low-risk group had a significantly better prognosis than the high-risk group. […] To validate the forecasting capabilities of the model we constructed, Cox regression analysis was performed. […] Different regression analyses showed that the model-based calculated risk score was an independent risk factor, with hazard ratios of 1.312 (1.2081.425) and 1.267 (1.1631.380), respectively.
  • #37 A disulfidptosis-related lncRNA index predicting prognosis and the tumor microenvironment in colorectal cancer | Scientific Reports
    https://www.nature.com/articles/s41598-023-47472-3
    The ROC curve showed that the risk score was the best predictor of prognosis among all the elements. […] Finally, the consistency index of the model showed that it performed significantly better than clinical characteristics such as sex, age and tumor stage. […] The above studies have suggested that the risk score has good predictive ability for prognosis. […] These findings provide new insights into the pathogenesis, treatment and prognosis of patients with CRC. […] Our model is a bioinformatics-based predictive model, which differs from other prognostic models in that it taps into tumor characteristics at the genetic level, largely circumventing the many limitations imposed by tumor heterogeneity. […] In this study, we constructed a novel predictive model based on disulfide-related lncRNAs aimed at accurately predicting patient prognosis.
  • #38 Nutritional and inflammatory measures predict survival of patients with stage IV colorectal cancer | BMC Cancer | Full Text
    https://bmccancer.biomedcentral.com/articles/10.1186/s12885-020-07560-3
    This study aimed to evaluate the prognostic impact of nutritional and inflammatory measures (controlling nutritional status (CONUT) score, prognostic nutritional index (PNI), and modified Glasgow prognostic score (mGPS)) on overall survival (OS) in patients with stage IV colorectal cancer (CRC). […] After adjusting for known factors (age, gender, BMI, ECOG performance status, location of primary tumor, CEA levels, histological type, M category, and prior surgical treatment), all three measures were found to be independent prognostic factors for OS in patients with stage (CONUT score, p0.001; PNI, p0.001; mGPS, p0.001). […] CONUT score, PNI, and mGPS were found to be independent prognostic factors for OS in patients with stage IV CRC, suggesting that nutritional and inflammatory status is a useful host-related prognostic indicator in stage IV CRC.
  • #39 Nutritional and inflammatory measures predict survival of patients with stage IV colorectal cancer | BMC Cancer | Full Text
    https://bmccancer.biomedcentral.com/articles/10.1186/s12885-020-07560-3
    In univariate analysis, CONUT score (p0.001), PNI (p0.001), and mGPS (p0.001), as well as gender (p=0.028), BMI (p=0.008), ECOG performance status (p0.001), location of primary tumor (p0.001), CEA levels (p0.001), histological type (p0.001), M category (p0.001), and surgical treatment (p0.001), were associated with prognosis. […] Multivariate analyses were performed, adjusting for clinical factors that were significant in univariate analyses (gender, BMI, ECOG performance status, location of primary tumor, CEA levels, histological type, M category, and surgical treatment); age was also included given the prior knowledge according to TNM eighth edition. All three measures were found to be independent prognostic factors for OS in patients with stage IV CRC (CONUT score, p0.001; PNI, p0.001; mGPS, p0.001). […] The present study revealed that CONUT score, PNI, and mGPS, which consist of these factors, are strongly correlated with prognosis in stage IV CRC patients.
  • #40 Nutritional and inflammatory measures predict survival of patients with stage IV colorectal cancer | BMC Cancer | Full Text
    https://bmccancer.biomedcentral.com/articles/10.1186/s12885-020-07560-3
    In univariate analysis, CONUT score (p0.001), PNI (p0.001), and mGPS (p0.001), as well as gender (p=0.028), BMI (p=0.008), ECOG performance status (p0.001), location of primary tumor (p0.001), CEA levels (p0.001), histological type (p0.001), M category (p0.001), and surgical treatment (p0.001), were associated with prognosis. […] Multivariate analyses were performed, adjusting for clinical factors that were significant in univariate analyses (gender, BMI, ECOG performance status, location of primary tumor, CEA levels, histological type, M category, and surgical treatment); age was also included given the prior knowledge according to TNM eighth edition. All three measures were found to be independent prognostic factors for OS in patients with stage IV CRC (CONUT score, p0.001; PNI, p0.001; mGPS, p0.001). […] The present study revealed that CONUT score, PNI, and mGPS, which consist of these factors, are strongly correlated with prognosis in stage IV CRC patients.
  • #41 Colorectal Cancer Survival Rates | Colorectal Cancer Prognosis | American Cancer Society
    https://www.cancer.org/cancer/types/colon-rectal-cancer/detection-diagnosis-staging/survival-rates.html
    Survival rates can give you an idea of what percentage of people with the same type and stage of cancer are still alive a certain amount of time (usually 5 years) after they were diagnosed. […] Keep in mind that survival rates are estimates and are often based on previous outcomes of large numbers of people who had a specific cancer, but they cant predict what will happen in any particular persons case. […] A relative survival rate compares people with the same type and stage of cancer to people in the overall population. […] The SEER database tracks 5-year relative survival rates for colon and rectal cancer in the United States, based on how far the cancer has spread. […] These numbers apply only to the stage of the cancer when it is first diagnosed. They do not apply later on if the cancer grows, spreads, or comes back after treatment.
  • #42 Colorectal Cancer Survival Rates | Colorectal Cancer Prognosis | American Cancer Society
    https://www.cancer.org/cancer/types/colon-rectal-cancer/detection-diagnosis-staging/survival-rates.html
    Survival rates can give you an idea of what percentage of people with the same type and stage of cancer are still alive a certain amount of time (usually 5 years) after they were diagnosed. […] Keep in mind that survival rates are estimates and are often based on previous outcomes of large numbers of people who had a specific cancer, but they cant predict what will happen in any particular persons case. […] A relative survival rate compares people with the same type and stage of cancer to people in the overall population. […] The SEER database tracks 5-year relative survival rates for colon and rectal cancer in the United States, based on how far the cancer has spread. […] These numbers apply only to the stage of the cancer when it is first diagnosed. They do not apply later on if the cancer grows, spreads, or comes back after treatment.
  • #43 Colorectal Cancer Survival Rates | Colorectal Cancer Prognosis | American Cancer Society
    https://www.cancer.org/cancer/types/colon-rectal-cancer/detection-diagnosis-staging/survival-rates.html
    Survival rates can give you an idea of what percentage of people with the same type and stage of cancer are still alive a certain amount of time (usually 5 years) after they were diagnosed. […] Keep in mind that survival rates are estimates and are often based on previous outcomes of large numbers of people who had a specific cancer, but they cant predict what will happen in any particular persons case. […] A relative survival rate compares people with the same type and stage of cancer to people in the overall population. […] The SEER database tracks 5-year relative survival rates for colon and rectal cancer in the United States, based on how far the cancer has spread. […] These numbers apply only to the stage of the cancer when it is first diagnosed. They do not apply later on if the cancer grows, spreads, or comes back after treatment.
  • #44 Colorectal Cancer Survival Rates | Colorectal Cancer Prognosis | American Cancer Society
    https://www.cancer.org/cancer/types/colon-rectal-cancer/detection-diagnosis-staging/survival-rates.html
    Survival rates can give you an idea of what percentage of people with the same type and stage of cancer are still alive a certain amount of time (usually 5 years) after they were diagnosed. […] Keep in mind that survival rates are estimates and are often based on previous outcomes of large numbers of people who had a specific cancer, but they cant predict what will happen in any particular persons case. […] A relative survival rate compares people with the same type and stage of cancer to people in the overall population. […] The SEER database tracks 5-year relative survival rates for colon and rectal cancer in the United States, based on how far the cancer has spread. […] These numbers apply only to the stage of the cancer when it is first diagnosed. They do not apply later on if the cancer grows, spreads, or comes back after treatment.
  • #45 Colorectal Cancer Survival Rates | Colorectal Cancer Prognosis | American Cancer Society
    https://www.cancer.org/cancer/types/colon-rectal-cancer/detection-diagnosis-staging/survival-rates.html
    Survival rates can give you an idea of what percentage of people with the same type and stage of cancer are still alive a certain amount of time (usually 5 years) after they were diagnosed. […] Keep in mind that survival rates are estimates and are often based on previous outcomes of large numbers of people who had a specific cancer, but they cant predict what will happen in any particular persons case. […] A relative survival rate compares people with the same type and stage of cancer to people in the overall population. […] The SEER database tracks 5-year relative survival rates for colon and rectal cancer in the United States, based on how far the cancer has spread. […] These numbers apply only to the stage of the cancer when it is first diagnosed. They do not apply later on if the cancer grows, spreads, or comes back after treatment.
  • #46 Colorectal Cancer Survival Rates | Colorectal Cancer Prognosis | American Cancer Society
    https://www.cancer.org/cancer/types/colon-rectal-cancer/detection-diagnosis-staging/survival-rates.html
    These numbers dont take everything into account. Survival rates are grouped based on how far the cancer has spread, but your age and overall health, whether the cancer started on the left or right side of the colon, if the cancer cells have certain gene or protein changes, how well the cancer responds to treatment, and other factors can also affect your outlook. […] People now being diagnosed with colon or rectal cancer may have a better outlook than these numbers show. Treatments improve over time, and these numbers are based on people who were diagnosed and treated at least 5 years earlier.
  • #47 Colorectal Cancer Survival Rates | Colorectal Cancer Prognosis | American Cancer Society
    https://www.cancer.org/cancer/types/colon-rectal-cancer/detection-diagnosis-staging/survival-rates.html
    These numbers dont take everything into account. Survival rates are grouped based on how far the cancer has spread, but your age and overall health, whether the cancer started on the left or right side of the colon, if the cancer cells have certain gene or protein changes, how well the cancer responds to treatment, and other factors can also affect your outlook. […] People now being diagnosed with colon or rectal cancer may have a better outlook than these numbers show. Treatments improve over time, and these numbers are based on people who were diagnosed and treated at least 5 years earlier.
  • #48 Risk factors and risk prediction models for colorectal cancer metastasis and recurrence: an umbrella review of systematic reviews and meta-analyses of observational studies
    https://pmc.ncbi.nlm.nih.gov/articles/PMC7318747/
    There is a clear need for systematic appraisal of models/factors predicting colorectal cancer (CRC) metastasis and recurrence because clinical decisions about adjuvant treatment are taken on the basis of such variables. […] Validating individual risk factors and even more so multivariable prediction models of multiple risk factors for local, regional, or distant metastasis and recurrence is crucially important as these could guide management of the primary tumor and provide prognostic information for patients and their cancer clinicians. […] This study provides an in-depth evaluation and cross-assessment of 51 risk factors and 24 prediction models. Our findings suggest that a minority of influential risk factors are employed in prediction models, which indicates the need for a more rigorous and systematic model construction process following evidence-based methods.
  • #49 Risk factors and risk prediction models for colorectal cancer metastasis and recurrence: an umbrella review of systematic reviews and meta-analyses of observational studies
    https://pmc.ncbi.nlm.nih.gov/articles/PMC7318747/
    There is a clear need for systematic appraisal of models/factors predicting colorectal cancer (CRC) metastasis and recurrence because clinical decisions about adjuvant treatment are taken on the basis of such variables. […] Validating individual risk factors and even more so multivariable prediction models of multiple risk factors for local, regional, or distant metastasis and recurrence is crucially important as these could guide management of the primary tumor and provide prognostic information for patients and their cancer clinicians. […] This study provides an in-depth evaluation and cross-assessment of 51 risk factors and 24 prediction models. Our findings suggest that a minority of influential risk factors are employed in prediction models, which indicates the need for a more rigorous and systematic model construction process following evidence-based methods.
  • #50 Risk factors and risk prediction models for colorectal cancer metastasis and recurrence: an umbrella review of systematic reviews and meta-analyses of observational studies
    https://pmc.ncbi.nlm.nih.gov/articles/PMC7318747/
    According to our pre-defined criteria for assessing the credibility of the evidence, only one risk factor was classified as convincing (vascular invasion for LNM in pT1 CRC), reflecting strong statistical significance and no hints of bias. […] Twelve (35%) of 34 probed risk factors for metastasis had an effect size suggesting 3-fold change in the odds of the outcome with p0.05. […] In regard to 17 probed risk factors for CRC recurrence, four (24%) had an effect size suggesting 3-fold change in the odds of the outcome with p0.05. None of them presented convincing evidence. […] Our findings suggest that efforts to address the limitations of the available evidence could be beneficial. Large-scale prospective studies are needed to generate evidence less prone to bias and allowing better predictive model building and validation.
  • #51 Risk factors and risk prediction models for colorectal cancer metastasis and recurrence: an umbrella review of systematic reviews and meta-analyses of observational studies
    https://pmc.ncbi.nlm.nih.gov/articles/PMC7318747/
    According to our pre-defined criteria for assessing the credibility of the evidence, only one risk factor was classified as convincing (vascular invasion for LNM in pT1 CRC), reflecting strong statistical significance and no hints of bias. […] Twelve (35%) of 34 probed risk factors for metastasis had an effect size suggesting 3-fold change in the odds of the outcome with p0.05. […] In regard to 17 probed risk factors for CRC recurrence, four (24%) had an effect size suggesting 3-fold change in the odds of the outcome with p0.05. None of them presented convincing evidence. […] Our findings suggest that efforts to address the limitations of the available evidence could be beneficial. Large-scale prospective studies are needed to generate evidence less prone to bias and allowing better predictive model building and validation.
  • #52 Risk factors and risk prediction models for colorectal cancer metastasis and recurrence: an umbrella review of systematic reviews and meta-analyses of observational studies
    https://pmc.ncbi.nlm.nih.gov/articles/PMC7318747/
    According to our pre-defined criteria for assessing the credibility of the evidence, only one risk factor was classified as convincing (vascular invasion for LNM in pT1 CRC), reflecting strong statistical significance and no hints of bias. […] Twelve (35%) of 34 probed risk factors for metastasis had an effect size suggesting 3-fold change in the odds of the outcome with p0.05. […] In regard to 17 probed risk factors for CRC recurrence, four (24%) had an effect size suggesting 3-fold change in the odds of the outcome with p0.05. None of them presented convincing evidence. […] Our findings suggest that efforts to address the limitations of the available evidence could be beneficial. Large-scale prospective studies are needed to generate evidence less prone to bias and allowing better predictive model building and validation.
  • #53 Risk factors and risk prediction models for colorectal cancer metastasis and recurrence: an umbrella review of systematic reviews and meta-analyses of observational studies
    https://pmc.ncbi.nlm.nih.gov/articles/PMC7318747/
    According to our pre-defined criteria for assessing the credibility of the evidence, only one risk factor was classified as convincing (vascular invasion for LNM in pT1 CRC), reflecting strong statistical significance and no hints of bias. […] Twelve (35%) of 34 probed risk factors for metastasis had an effect size suggesting 3-fold change in the odds of the outcome with p0.05. […] In regard to 17 probed risk factors for CRC recurrence, four (24%) had an effect size suggesting 3-fold change in the odds of the outcome with p0.05. None of them presented convincing evidence. […] Our findings suggest that efforts to address the limitations of the available evidence could be beneficial. Large-scale prospective studies are needed to generate evidence less prone to bias and allowing better predictive model building and validation.
  • #54 Transcription factor expression as a predictor of colon cancer prognosis: a machine learning practice | BMC Medical Genomics | Full Text
    https://bmcmedgenomics.biomedcentral.com/articles/10.1186/s12920-020-00775-0
    Colon cancer is one of the leading causes of cancer deaths in the USA and around the world. […] Overall, our results prove our prediction model has a strong prediction power on colon cancer prognosis. […] Transcription factors can be used to construct colon cancer prognostic signatures with strong prediction power. […] Our five TF-based predictive model would help with understanding the hidden relationship between colon cancer patient survival and transcription factor activities. […] The prediction power of our model is validated on hundreds of colon cancer patient samples available in the GEO database. […] The results showed that our model has a good predicting power in predicting colon cancer overall survival. […] Our predictive model and its biological functions would provide more insights in the precision treatment of colon cancer, which leads to further investigation on these five TF genes and their roles during the development of colon cancer at the molecular level.
  • #55
    https://link.springer.com/article/10.1186/s13148-025-01882-4
    Low NAT1 expression in CRC tumor tissues, relative to adjacent normal tissues, is significantly associated with a poorer patient prognosis. […] The Kaplan-Meier survival analysis revealed a significant association between reduced NAT1 expression and poorer outcomes in CRC patients, as evidenced by worse overall survival (P=0.00046), disease-free survival (P=0.00075), and progression-free survival (P=0.0013). […] Low NAT1 expression is associated with decreased responsiveness to chemotherapies in breast cancer patients. […] In this study, we demonstrated that NAT1 deficiency in colorectal cancer (CRC) cells increases resistance to multiple chemotherapeutic agents, including vinblastine, docetaxel, gemcitabine, vincristine, and daporinad. […] Importantly, overexpression of NAT1 in these cells restored sensitivity to all five drugs, providing strong evidence that NAT1 deficiency is a key factor driving resistance to these therapeutic agents in CRC.
  • #56
    https://link.springer.com/article/10.1186/s13148-025-01882-4
    Low NAT1 expression in CRC tumor tissues, relative to adjacent normal tissues, is significantly associated with a poorer patient prognosis. […] The Kaplan-Meier survival analysis revealed a significant association between reduced NAT1 expression and poorer outcomes in CRC patients, as evidenced by worse overall survival (P=0.00046), disease-free survival (P=0.00075), and progression-free survival (P=0.0013). […] Low NAT1 expression is associated with decreased responsiveness to chemotherapies in breast cancer patients. […] In this study, we demonstrated that NAT1 deficiency in colorectal cancer (CRC) cells increases resistance to multiple chemotherapeutic agents, including vinblastine, docetaxel, gemcitabine, vincristine, and daporinad. […] Importantly, overexpression of NAT1 in these cells restored sensitivity to all five drugs, providing strong evidence that NAT1 deficiency is a key factor driving resistance to these therapeutic agents in CRC.
  • #57
    https://link.springer.com/article/10.1186/s13148-025-01882-4
    Our findings extend these observations by demonstrating that treatment with vinblastine, docetaxel, gemcitabine, vincristine, or daporinad is associated with decreased NAT1 levels in CRC cell lines. […] These observations imply that reduced NAT1 expression enhances chemo-resistance by promoting the formation of LGR5+ CSCs. […] Our study shows that NAT1 primarily regulates metabolic pathways. […] Our results indicate that reduced NAT1 expression, which shifts cellular metabolism towards glycolysis, likely drives the development of LGR5+ CSCs and their chemo-resistance. […] Our research shows that suppressing NAT1 expression increases VEGFA expression in CRC cells. This amplifies VEGFA-VEGFR signaling between tumor cells and endothelial cells, promoting angiogenesis by activating endothelial cells. […] Our analysis using the TIMER2.0 database shows that reduced NAT1 expression is linked to lower infiltration of these cells, which may reduce the therapeutic effect of anti-PD-1 therapy.
  • #58
    https://link.springer.com/article/10.1186/s13148-025-01882-4
    Our findings extend these observations by demonstrating that treatment with vinblastine, docetaxel, gemcitabine, vincristine, or daporinad is associated with decreased NAT1 levels in CRC cell lines. […] These observations imply that reduced NAT1 expression enhances chemo-resistance by promoting the formation of LGR5+ CSCs. […] Our study shows that NAT1 primarily regulates metabolic pathways. […] Our results indicate that reduced NAT1 expression, which shifts cellular metabolism towards glycolysis, likely drives the development of LGR5+ CSCs and their chemo-resistance. […] Our research shows that suppressing NAT1 expression increases VEGFA expression in CRC cells. This amplifies VEGFA-VEGFR signaling between tumor cells and endothelial cells, promoting angiogenesis by activating endothelial cells. […] Our analysis using the TIMER2.0 database shows that reduced NAT1 expression is linked to lower infiltration of these cells, which may reduce the therapeutic effect of anti-PD-1 therapy.
  • #59
    https://link.springer.com/article/10.1186/s13148-025-01882-4
    Our findings extend these observations by demonstrating that treatment with vinblastine, docetaxel, gemcitabine, vincristine, or daporinad is associated with decreased NAT1 levels in CRC cell lines. […] These observations imply that reduced NAT1 expression enhances chemo-resistance by promoting the formation of LGR5+ CSCs. […] Our study shows that NAT1 primarily regulates metabolic pathways. […] Our results indicate that reduced NAT1 expression, which shifts cellular metabolism towards glycolysis, likely drives the development of LGR5+ CSCs and their chemo-resistance. […] Our research shows that suppressing NAT1 expression increases VEGFA expression in CRC cells. This amplifies VEGFA-VEGFR signaling between tumor cells and endothelial cells, promoting angiogenesis by activating endothelial cells. […] Our analysis using the TIMER2.0 database shows that reduced NAT1 expression is linked to lower infiltration of these cells, which may reduce the therapeutic effect of anti-PD-1 therapy.
  • #60
    https://link.springer.com/article/10.1186/s13148-025-01882-4
    Our findings extend these observations by demonstrating that treatment with vinblastine, docetaxel, gemcitabine, vincristine, or daporinad is associated with decreased NAT1 levels in CRC cell lines. […] These observations imply that reduced NAT1 expression enhances chemo-resistance by promoting the formation of LGR5+ CSCs. […] Our study shows that NAT1 primarily regulates metabolic pathways. […] Our results indicate that reduced NAT1 expression, which shifts cellular metabolism towards glycolysis, likely drives the development of LGR5+ CSCs and their chemo-resistance. […] Our research shows that suppressing NAT1 expression increases VEGFA expression in CRC cells. This amplifies VEGFA-VEGFR signaling between tumor cells and endothelial cells, promoting angiogenesis by activating endothelial cells. […] Our analysis using the TIMER2.0 database shows that reduced NAT1 expression is linked to lower infiltration of these cells, which may reduce the therapeutic effect of anti-PD-1 therapy.

Zobacz więcej

inwazja naczyń limfatycznych przeżycie całkowite mutacja BRAF mutacja KRAS komórki macierzyste nowotworu przerzut odległy perforacja rak niemetastatyczny inwazja naczyniowa glikoliza wskaźnik CONUT antygen karcinoembrionalny rak drobnokomórkowy nomogram niestabilność mikrosatelitarna rak okrężnicy gruczolakorak śluzowy stopień zróżnicowania przeżycie bez choroby niedrożność jelit rak odbytnicy rak jelita grubego terapia anty-PD-1