Evaluating prognostic factors in colorectal cancer begins in the lab by analyzing bio-samples.

Prognostic factors in Colorectal Cancer

Cancer staging

The outcome in patients with cancer is determined by a combination of numerous factors. The personalized treatment of a cancer patient depends on the site of origin of the cancer, the morphologic type, and prognostic factors specific to the particular patient and cancer. While this blog post focuses on prognostic factors in colorectal cancer, it’s helpful to know about the immense influence prognostic factors have on cancer outcome in general (Gospodarowicz & O’sullivan, 2003). According to the TNM project committee, prognostic factors are classified into three groups.

  1. Tumor-related prognostic factors that directly relate to the tumor itself
  2. Host-related prognostic factors include inherent demographic characteristics such as age, gender, race, performance status, comorbidity, and immune status
  3. Environment-related prognostic factors such as choice of treatment, quality of treatment, access to care, or health-care policy (Gospodarowicz & O’sullivan, 2003)

Colorectal cancer accounts for nearly 1 mio deaths in 2020

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers worldwide. Although the overall survival has risen due to new treatments and drugs, CRC is still one of the leading causes of cancer-related death (Martins et al., 2019; Divitiis et al., 2014). According to GLOBOCAN data, in 2020, there were an estimated 19.3 million new cases and 10 million cancer deaths worldwide, of which CRC contributed about 1.93 million (10 %) further incidences and 0.94 million (9.4 %) deaths (Hossain et al., 2022). As early diagnosis of CRC is entirely treatable, accurate determination of tumor-related prognostic factors is of infinite importance.

TNM classification

The development of CRC is related to non-modifiable host- and environmental factors, such as age, gender, race, family history, or rare inherited conditions (Hossain et al., 2022). However, to plan the treatment of an individual CRC patient, tumor-related prognostic factors like growth, invasion, and metastasis are fundamental (Gospodarowicz & O’sullivan, 2003). For this reason, the stage of the cancer is determined via the internationally accepted TNM classification.

  • The T(umor) category describes the primary tumor site and size,
  • The N(node) category describes the regional lymph node involvement
  • The M(etastasis) category describes the metastatic spread.

AJCC Cancer Staging Manual, 8th Edition (2017), published by Springer International Publishing.

In addition, numbers describe in more detail if and how much cancer is in the body. The earliest stage CRC can have is stage 0, then range from stages I (1) through IV (4). Altogether, combined T, N, and M categories provide detailed information about the stage groups for CRC summarized in the above figure and described in more detail in the following table.

0“Cancer in situ”. The cancer cells are only in the mucosa, or the inner lining, of the
colon or rectum.
IThe cancer has grown through the mucosa and has invaded the muscular layer of
the colon or rectum. It has not spread into nearby tissue or lymph nodes (T1 or T2,
N0, M0).
IIAThe cancer has grown through the wall of the colon or rectum but has not spread
to nearby tissue or to the nearby lymph nodes (T3, N0, M0).
IIBThe cancer has grown through the layers of the muscle to the lining of the
abdomen, called the visceral peritoneum. It has not spread to the nearby lymph
nodes or elsewhere (T4a, N0, M0).
IICThe cancer has spread through the wall of the colon or rectum and has grown into
nearby structures. It has not spread to the nearby lymph nodes or elsewhere (T4b,
N0, M0).
IIIAThe cancer has grown through the inner lining or into the muscle layers of the
intestine. It has spread to 1 to 3 lymph nodes or to a nodule of tumor cells in
tissues around the colon or rectum that do not appear to be lymph nodes, but has
not spread to other parts of the body (T1 or T2, N1 or N1c, M0; or T1, N2a, M0).
IIIBThe cancer has grown through the bowel wall or to surrounding organs and into 1
to 3 lymph nodes or to a nodule of tumor in tissues around the colon or rectum
that do not appear to be lymph nodes. It has not spread to other parts of the
body (T3 or T4a, N1 or N1c, M0; T2 or T3, N2a, M0; or T1 or T2, N2b, M0).
IIICThe cancer of the colon, regardless of how deep it has grown, has spread to 4 or
more lymph nodes but not to other distant parts of the body (T4a, N2a, M0; T3 or
T4a, N2b, M0; or T4b, N1 or N2, M0).
IVAThe cancer has spread to a single distant part of the body, such as the liver or
lungs (any T, any N, M1a).
IVBThe cancer has spread to more than 1 part of the body (any T, any N, M1b).
IVCThe cancer has spread to the peritoneum. It may also have spread to other sites or
organs (any T, any N, M1c).
Overview of CRC stages


Apart from tumor growth, invasion, and metastasis, biological markers (biomarkers) also reveal significant information about a person’s cancer. Biomarkers are genes, proteins, or other substances that can be measured in blood, tissue, or other fluids functioning as indicators of pathogenic processes, or pharmacologic responses to a therapeutic intervention. The most common prognostic biomarkers in CRC used for diagnosis, progression, prognosis, and treatment are summarized in the following figure.

BiomarkerPrevalenceFunctionMutationHeritabilityTreatment option
BRAF10-15 % of patientsStimulates growth and division of cellsMutation causes uncontrolled growth of cells, which cannot be
turned off
Not hereditary
(not a germline mutation) →
will not pass from one generation to another.
The BRAF V600E mutation is a prognostic biomarker of aggressive
tumor growth. Patients need aggressive treatment with chemotherapy.
Patients can receive BRAF inhibitors given together with additional
inhibitors as a second or third line therapy
KRAS40-45 % of patientsActs as an “on/off” switch that instructs cells to grow and divide or matureThe KRAS gene is an oncogene →
mutations cause normal cells to become cancerous.
Patients with mutated or unknown KRAS status should receive
chemotherapy including FOLFOX, CAPOX, or FOLFIRI with
or without bevacizumab.
Patients should not receive EGFR-inhibitors like cetuximab
or panitumumab alone or in combination with chemotherapy
NRAS5 % of patientsActs as an “on/off” switch to monitor cell growth, division, and movementMutation causes the protein to be locked in the “on” position
driving constant and uncontrolled cell division
Patients should receive chemotherapy (some examples are FOLFOX,
CAPOX, and FOLFIRI), with or without Bevacizumab
HER23-4 % of patientsReceptor on the surface of almost all the cells in our body.
It is responsible for the communication between the cells
to promote their growth, division, repair, and survival
Mutation causes overexpression resulting in too many
HER2 receptors → uncontrolled growth and division of cells
Treatment with dual-targeted therapy against HER2 →
combination of trastuzumab with either pertuzumab
or lapatinib alone or with chemotherapy
NTRK< 1 % of patientsTRK proteins are receptors mostly found on the surface of cells
of the nervous system receiving signals from neighboring
neurons to instruct cells to grow and divide
NTRK genes can fuse with other non-related genes producing new
NTRK fusion proteins that promote uncontrolled cell growth
and division in cancer cells
Treatment with one of two FDA-approved NTRK inhibitors:
larotrectinib or entrectinib
MSI-H15 % of patientsMicrosatellites (MS) are short repetitive DNA sequences providing
instructions for our cells on how to grow, carry out specific activities,
divide, or die → number of microsatellite repeats has to remain
the same in all cells guaranteed by the DNA mismatch repair (MMR) process
cancer cells are “deficient” in mismatch repair (MMR) 
→ tumor cells end up with too many microsatellite DNA repeats
→ high microsatellite instability (MSI-H)
Treatment with immune checkpoint inhibitors
(Pembrolizumab and/or Nivolumab)
UGT1A145 % of African patients
31 % of European patients
The protein UDP glucuronosyltransferases is an enzyme
that is most active in the liver and converts toxic irinotecan (chemotherapy drug)
to a non-toxic form
Patients with a UGT1A1 mutation cannot convert toxic irinotecan’s
leading to severe toxicity (especially liver toxicity)
Germline mutation →
will pass from one generation to another
Irinotecan is a chemotherapy drug commonly used to treat
metastatic CRC → Patients experience severe toxicity
during treatment with FOLFIRI, FOLFIRINOX, or irinotecan alone
PIK3CA10-20 % of patientsProtein is part of an enzyme called phosphatidylinositol 3-kinase (PI3K)
→ PI3K promotes and regulates cell proliferation, migration or movement,
apoptosis and survival
Mutation drives the growth of cells.Not
Patients should receive standard chemotherapy such as:
FOLFOX, CAPOX, or FOLFIRI with or without bevacizumab
DPYD5-18 % of patientsProtein converts toxic fluorouracil-based (chemotherapy drugs
used in colorectal cancer treatment) to a non-toxic molecule which
can be removed from the body.
Patients with a gene mutation either have a less efficient enzyme
or complete loss of the enzyme
→ no metabolization of chemotherapy drugs possible
Germline mutation →
will pass from one generation to another
Patients cannot metabolize fluoropyrimidine-based chemotherapies
(FOLFOX, FOLFIRI, FOLFIRINOX, capecitabine, and TAS-102).
Patients with less-efficient enzyme activity experience severe
side effects like neutropenia, diarrhea, and mucositis.
Patients with no enzyme activity at all may experience
life-threatening complications.
PTCH14-5 % of patientsTumor suppressor gene that is part of the hedgehog signaling pathwayMutations cause loss of protein function
→ hedgehog signaling pathway leads to cancerous cells
and tumor growth.
No FDA approved therapies targeting PTCH1 mutations to date
CRC biomarkers by the Colorectal Cancer Alliance

Digital pathology

Digital pathology plays a key role in the diagnosis of prognostic factors in oncological diseases. Pathologists have to evaluate a large amount of histological data with steadily growing case numbers. Here, Artificial Intelligence (AI) offers the possibility to compensate the increasing challenges by supporting the pathologist in their daily routines. For instance, AI could be used to perform repetitive tasks such as the analysis of multiple slides of lymph node biopsies to detect (micro) metastases. In addition, it could already been shown that tumor grading and characterization of an invasive tumor front is more precise and reliable if AI was used. Other works have displayed that even genetic mutations, in particular MSI, can be predicted directly from the HE slide.

The transfer of AI solutions to pathology can enable a reduction in workload as it analyzes more data in less time without producing biases. Our MICAIA® pathology software offers the ideal computational support to address your individual image analysis tasks. Use the preinstalled AI-based apps to view, annotate, process and analyze your single or whole-slide images in brightfield or fluorescence. If you are missing a feature or require an individual analysis services, we will help you to achieve your research goals. 

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Nathalie Falk

Nathalie is a molecular biologist with a PhD in neurobiology and postdoctoral experience in immunology and nephrology. After changing fields, she is currently studying psychology and gaining experience in content creation at Fraunhofer IIS.

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