Mars and Venus- Do Men and Women Respond Differently to Cancer Immunotherapy?
By Sahana Shankar, Ph.D. candidate
Sex-associated differences in physiology, psychology, immunology is a point of interest for scientists and the general public alike. Recent research suggests that the difference lies in the varied immune responses in men and women to different cancers.
Studies focusing on sex-differences in disease have suggested that men and women vary in symptoms, severity, age of onset, and prevalence for a wide variety of diseases. For example, women are more at risk for autoimmune disorders than men and are more resistant to viral respiratory infections.
Cancer has evolved into one of the leading causes of death worldwide due to extended lifespan. Some data exists for gender-based susceptibility to certain types of cancer. For example, hematological malignancies are more prevalent in males and thyroid cancers are more common in females. However, there is not much information on sex-associated differences in response to cancer therapy. It is widely reported that men and women digest drugs differently due to subtle changes in physiology. Hence, it is imperative to understand if there is any variation in response to cancer therapy.
Immune Checkpoint Blockade
A common and broad-spectrum therapy for cancer is Immune Checkpoint Blockade (ICB). Essentially, ICB therapy is aimed at inhibiting tumor-specific markers that are known to enhance tumor progression, suppress immune response or cause cytotoxicity of neighboring cells. The commonly known tumor biomarkers are
- TMB- tumor mutation burden: total number of non-synonymous mutations in the coding exome
- neoantigen load- number of tumor-specific antigens
- T-cell and B-cell receptors in response to the tumor at the tumor microenvironment
- Immune checkpoints- a wide variety of genes and thereby proteins expressed in response to a tumor. Analyzing the gene expression profiles of these is a good indicator of tumor progression.
- Increased Immune cell population- activated CD4+ T cells, CD8+ T cells, regulatory T cells, etc
- aneuploidy score- chromosome number variation is associated with many cancers
A collaborative study involving a team of researchers at The University of Texas MD Anderson Cancer Center, Houston and Xiangya Hospital, Central South University, China investigated the molecular differences in these biomarkers and the efficacy of their inhibition between male and female cancer patients due to ICB.
Previous meta-analyses of clinical trial data from a wide variety of cancer studies showed that female patients had a better overall survival (OS) advantage. In this study, reclassifying previous clinical trial data sets with different selection criteria showed no significant advantage in male or female patients suggesting that indiscriminately pooling clinical trial data may not be informative. If clinical trials were grouped based on biomarkers in response to different cancer types, there were significant sex differences. They found that inconsistencies also arise from (a) the control arm of clinical trials in some studies that use placebo controls and others use docetaxel, a standard chemotherapy drug; (b) insignificant correlation of single immune marker with cancer type in pooled clinical trials due to inconsistent values from each trial.
To address the shortcomings of pooled clinical trial analyses, the authors assessed clinical outcomes, overall survival, response and molecular differences across all male and female patients who received ICB therapy. Male patients showed better survival advantage against certain cancers (colorectal or glioblastoma) and female patients against others (esophagogastric or lung adenocarcinomas). Females with Non-small cell lung carcinoma responded particularly well to IBC (50% response rate vs 25% in males). Looking at specific biomarkers, they found higher TMB in male patients with melanoma and high neoantigen load in male patients with bladder cancer. Based on these preliminary data from ICB clinical trials, they expanded their analyses to larger sample size to check for statistical significance in sex-based differences in biomarkers.
A comprehensive analysis of male and female patients from The Cancer Genome Atlas (TGCA) afforded a large sample size to check for molecular differences in 6 major biomarkers across 22 cancer types with at least 20 samples for males and females. To refine the data and make it statistically significant, the authors used a propensity score algorithm to reduce and reweight potential confounding effects. In some cancers such as kidney renal papillary cell carcinoma and melanoma, there was a male bias in immune response whereas in some others like lung squamous cell carcinoma (LUSC), there was a female bias. In male patients with melanoma or KIRP, there was increased TMB and neoantigen load, higher abundance of immune cells and expression of immune checkpoints. In female patients with LUSC, there was an abundance of activated T cell receptors, CD4+ and CD8+ T cells, lower aneuploidy. Some features were common such as higher cytotoxic activity and expression of immune checkpoints but varied among genders within the same cancer type, suggesting a clear divergence in the therapeutic immune response. To validate the same, they divided the large data set from TCGA into multiple independent datasets and observed similar results.
This study shows that methodology, sample size, number of variable parameters considered and relevant computational tools play crucial roles in informing meta-analyses. The strategized reclassification according to molecular markers demonstrates a clear difference in gender effects between melanoma and lung cancers, the cancer types with the largest number of ICB clinical trials. Attributing sex-associated differences to cancer immunotherapy is challenging due to social, cultural and physical variables such as lifestyle, behavior differences, access to therapy, age of onset, smoking status, etc. However, this team makes a concerted and exhaustive effort to tease out valuable biological information from a labyrinth of omics data. It can provide a basis for future studies to discover sex-related responses to anti-cancer drugs.
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