Rectal cancer is a form of colorectal cancer arising in the last section of the large intestine. Locally advanced cases are typically treated with neoadjuvant therapy - treatment given before surgery to shrink the tumor and reduce the chance of cancer returning.
Neoadjuvant treatment options include long-course chemoradiotherapy (combining chemotherapy drugs with radiation over several weeks), short-course radiotherapy, or total neoadjuvant therapy (TNT), where all systemic chemotherapy is given before surgery.
The goal of neoadjuvant treatment is tumor downstaging - making the tumor smaller and reducing its spread to lymph nodes so that surgery is more effective and complete surgical removal of the rectum may even be avoided in the best cases.
A key outcome measure is pathological complete response (pCR), which means no living cancer cells are found when the removed tissue is examined under a microscope after neoadjuvant treatment. Achieving pCR is associated with much better long-term outcomes.
The tumor immune microenvironment (TIME) refers to all the immune cells, molecules, and signals that surround a tumor. Rather than being passive bystanders, these immune cells actively shape how the tumor grows and how well it responds to treatment.
Key immune cell types found within tumors include CD8+ cytotoxic T lymphocytes (which directly kill cancer cells), CD4+ helper T cells (which coordinate immune responses), FOXP3+ regulatory T cells (which dampen immune activity), and tumor-associated macrophages (TAMs, which can either support or suppress anti-tumor responses).
PD-L1 (programmed death-ligand 1) is a protein that cancer cells and immune cells can express to put the brakes on immune attacks. Its presence in a tumor has complex implications - in some situations it signals an already active immune response trying to prevent excessive inflammation.
Researchers study these components by analyzing pretreatment biopsies - small tissue samples taken from the tumor before any treatment begins - using techniques like immunohistochemistry, which stains specific proteins to make them visible under a microscope.
This study is a systematic review, meaning the researchers rigorously searched multiple scientific databases (PubMed, Embase, and Cochrane Library) to find all relevant published studies on this topic, rather than conducting new experiments themselves.
The search focused on studies examining the relationship between pretreatment immune biomarkers in rectal tumor biopsies and how well patients responded to neoadjuvant treatment. Only studies that measured immune markers before treatment and tracked tumor regression outcomes were included.
Studies were excluded if they used concurrent immunotherapy alongside standard chemoradiotherapy, because such drugs would directly alter the immune environment and make it impossible to interpret the baseline immune profile's predictive value.
The QUIPS tool (Quality in Prognostic Studies) was used to assess the risk of bias in each included study, evaluating factors like how patients were selected, how immune markers were measured, and whether statistical methods were sound.
Fifteen studies covering 2,356 patients were included in the final analysis. Study designs were mostly retrospective - meaning they looked back at existing patient records - and cohort sizes ranged from 24 to 298 patients. Most patients had stage II or III rectal cancer.
The most commonly studied immune biomarker was CD8+, appearing in nine of the fifteen studies. Other biomarkers examined included total tumor-infiltrating lymphocytes (TILs), CD4+ T cells, FOXP3+ regulatory T cells, CD163+ macrophages, CD68+ macrophages, PD-1+, PD-L1, and natural killer (NK) cells.
Biomarkers were quantified using various approaches: manual counting under a microscope, automated computer-based image analysis, RNA sequencing, and proteomic profiling. This variability in measurement methods made direct comparisons across studies challenging.
Tumor regression was measured in two main ways: by whether patients achieved pCR (complete absence of tumor), or by a standardized tumor regression grade (TRG) score, which categorizes the degree of tumor shrinkage on a scale.
The strongest finding of this review was a consistent positive association between CD8+ T cell density and better tumor regression. Of nine studies examining CD8+, seven found a statistically significant link between higher CD8+ density in pretreatment biopsies and improved response to neoadjuvant therapy.
One study found a particularly strong correlation with a confidence interval of 0.07-0.76 (p less than 0.001), and another demonstrated an odds ratio of 1.47-4.99 (p = 0.002), both indicating that patients with more CD8+ T cells had substantially better treatment responses.
Similarly, all four studies assessing total tumor-infiltrating lymphocytes (TILs) - despite using different measurement methods - found a significant positive association with tumor regression, reinforcing that an immune-active tumor environment is beneficial.
PD-L1 and PD-1+ expression also showed associations with better treatment response in some studies, though findings were less consistent. PD-L1 on immune cells may indicate an ongoing immune activation rather than simply immune suppression.
FOXP3+ regulatory T cells (Tregs) are immune cells that suppress other immune responses. Three studies examined whether high densities of these cells might predict poorer treatment response, and only one found a statistically significant negative association.
The inconsistency in FOXP3+ findings may be partly explained by differences in measurement methods: one study expressing results as a percentage of all positive cells (influenced by other immune cell types) versus others using absolute cell counts per square millimeter.
CD163+ macrophages represent a type of macrophage known as the M2 phenotype, which typically promotes anti-inflammatory and tissue-repair activities rather than anti-tumor killing. One of two studies found these cells significantly associated with limited tumor regression.
Natural killer (NK) cells and CD68+ macrophages (a general macrophage marker) were each only studied once and showed no significant association with treatment response, making it impossible to draw conclusions about their predictive value.
CD8+ cytotoxic T cells are widely recognized as the primary killers of cancer cells in the immune system. They recognize cancer-specific proteins on tumor cell surfaces and directly destroy those cells, explaining why high levels before treatment predict better outcomes after chemoradiotherapy.
Interestingly, CD4+ helper T cells - which also fall under the TIL category - were not significantly associated with treatment response in any of the three studies that examined them. This suggests a specific anti-tumor mechanism unique to CD8+ cells rather than a general TIL effect.
One explanation is that some CD4+ subtypes can actually help tumors - for example, Th2 cells release cytokines (IL-4, IL-5, IL-13) that have been linked to tumor survival. The studies reviewed here did not distinguish between different CD4+ subtypes, which may have masked any beneficial CD4+ effect.
The regulatory T cells (FOXP3+) and M2 macrophages (CD163+) appear to counter the anti-tumor effects of CD8+ cells - potentially by suppressing cytotoxic T lymphocyte activity and promoting blood vessel growth that feeds the tumor rather than helping immune cells kill it.
A major limitation of this field is the lack of standardized protocols for measuring immune biomarkers. Different studies used different antibodies, different scoring thresholds for what counts as "high" versus "low," and different methods (manual vs. automated counting).
Treatment heterogeneity is another confounding factor - patients in different studies received different chemotherapy drug combinations, radiation doses, and treatment schedules. Since treatment type itself influences response rates, comparing biomarker effects across studies is challenging.
Many studies used a simple pCR versus non-pCR dichotomy that misses the more nuanced spectrum of partial responses captured by tumor regression grading. This oversimplification may cause some meaningful partial responses to be missed in statistical analyses.
The retrospective design of most included studies means they depended on existing tissue samples and records, which introduces potential biases in patient selection and may not fully represent the range of patients seen in clinical practice.
CD8+ T cell infiltration in pretreatment biopsies has emerged as the most promising candidate biomarker for predicting response to neoadjuvant therapy in rectal cancer - a finding that aligns with the well-established role of CD8+ cells in the established "immunoscore" prognostic system for colorectal cancer.
If validated in larger prospective studies, measuring CD8+ density before treatment could help identify which patients are most likely to achieve pathological complete response, potentially allowing these patients to avoid surgery entirely and preserve their rectum and bowel function.
For patients with low CD8+ infiltration, this biomarker could identify those who need more intensive treatment strategies or novel approaches to activate their immune system - possibly including immunotherapy drugs that boost CD8+ activity.
Future research should focus on prospective studies with standardized measurement protocols, larger patient cohorts, and serial biopsies taken during treatment to understand how the immune microenvironment changes and whether those changes predict final outcomes.