Implementing TMB measurement in clinical practice: considerations on assay requirements

Nano-enabled regulation of DNA damage in tumor cells to enhance neoantigen-based pancreatic cancer immunotherapy

Low-expression antigens, especially neoantigens, pose a significant challenge in immunotherapy for low immunogenicity pancreatic cancer. Increasing the tumor mutation burden is crucial to enhance the expression of tumor antigens and improve tumor immunogenicity. However, the incomplete intervention in DNA stability hampers effective elevation of the tumor mutation burden, thus reducing the probability of neoantigen. To address this issue, we have developed a novel nano-regulator that intervenes in the DNA stability of tumor cells, thereby enhancing tumor mutations. This nano-regulator comprises metal-organic frameworks (MOFs) encapsulating DNA damage agent doxorubicin and DNA damage repair inhibitor siRNA-ATR, enabling simultaneous induction of DNA mutations and inhibition of their repair. Importantly, this regulator, named as MOFDOX&siATR, can modulate the tumor gene expression profile, induce the production of neoantigens of Atp8b1, and enhance the immunogenicity of pancreatic cancer. The characteristics of DNA stability intervention by MOFDOX&siATR hold promise for augmenting the immune response in low immunogenic tumors, making it a potential nanomedicine for the treatment of pancreatic cancer.

Blockade of glucose-6-phosphate dehydrogenase induces immunogenic cell death and accelerates immunotherapy

BACKGROUND

Enhanced glucose metabolism has been reported in many cancers. Glucose-6-phosphate dehydrogenase (G6PD) is a rate-limiting enzyme involved in the pentose phosphate pathway, which maintains NADPH levels and protects cells from oxidative damage. We recently found that low G6PD expression correlates with active tumor immunity. However, the mechanism involving G6PD and tumor immunity remained unclear.

METHODS

We conducted in vitro studies using G6PD-knocked down malignant melanoma cells, pathway analysis using the GEO dataset, in vivo studies in combination with immune checkpoint inhibitors (ICIs) using a mouse melanoma model, and prognostic analysis in 42 melanoma patients and 30 lung cancer patients who were treated with ICIs.

RESULTS

Inhibition of G6PD, both chemically and genetically, has been shown to decrease the production of NADPH and reduce their oxidative stress tolerance. This leads to cell death, which is accompanied by the release of high mobility group box 1 and the translocation of calreticulin to the plasma membrane. These findings suggested that inhibiting G6PD can induce immunogenic cell death. In experiments with C57BL/6 mice transplanted with G6PD-knockdown B16 melanoma cells and treated with anti-PD-L1 antibody, a significant reduction in tumor size was observed. Interestingly, inhibiting G6PD in only a part of the lesions increased the sensitivity of other lesions to ICI. Additionally, out of 42 melanoma patients and 30 lung cancer patients treated with ICIs, those with low G6PD expression had a better prognosis than those with high G6PD expression (p=0.0473; melanoma, p=0.0287; lung cancer).

CONCLUSION

G6PD inhibition is a potent therapeutic strategy that triggers immunogenic cell death in tumors, significantly augmenting the efficacy of immunotherapies.

A pan-cancer analysis of the core pre-mRNA 3' end processing factors, and their association with prognosis, tumor microenvironment, and potential targets

Alternative polyadenylation (APA) is a crucial mechanism for regulating gene expression during pre-mRNA 3' processing. Pre-mRNA 3' end processing factors is the main factor involved in this process. However, pre-mRNA 3' end processing factors in different cancer expression profiles and the relationship between pre-mRNA 3' end processing factors and tumor microenvironment and the prognosis of the same patient is still unclear. In this study, we conducted a comprehensive exploration of the core pre-mRNA 3' end processing factors across various cancer types by utilizing common cancer database, and revealing a robust correlation between the expression of these core factors and tumor characteristics. Leveraging advanced bioinformatics databases, we evaluated the expression levels and prognostic relevance of pre-mRNA 3' end processing factors across pan-cancer tissues. Our extensive pan-cancer analysis revealed unique expression patterns of pre-mRNA 3' end processing factors in both tumor and adjacent non-tumorous tissues. Notably, we found a significant correlation between the expression levels of pre-mRNA 3' end processing factors and patient prognosis. Furthermore, we identified strong associations between pre-mRNA 3' end processing factors expression and various factors, such as stromal, immune, RNA stemness, and DNA stemness scores across pan-cancer tissues. Our data also highlighted a link between the expression of pre-mRNA 3' end processing factors and sensitivity to specific drugs, including pyrazoloacndine, amonaflide, and chelerythrinede, among others. We found four key pre-mRNA 3' end processing factors that play a crucial role in mRNA preprocessing. Our study illuminates the potential promotion and inhibition role of pre-mRNA 3' end processing regulators in the progression of cancer, CPSF2, CPSF3, CSTF2, SYMPK offering valuable insights for future research investigations on these regulators as diagnostic markers and therapeutic targets across pan-cancer.

Mechanism of immune activation mediated by genomic instability and its implication in radiotherapy combined with immune checkpoint inhibitors

Various genetic and epigenetic changes associated with genomic instability (GI), including DNA damage repair defects, chromosomal instability, and mitochondrial GI, contribute to development and progression of cancer. These alterations not only result in DNA leakage into the cytoplasm, either directly or through micronuclei, but also trigger downstream inflammatory signals, such as the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) signaling pathway. Apart from directly inducing DNA damage to eliminate cancer cells, radiotherapy (RT) exerts its antitumor effects through intracellular DNA damage sensing mechanisms, leading to the activation of downstream inflammatory signaling pathways. This not only enables local tumor control but also reshapes the immune microenvironment, triggering systemic immune responses. The combination of RT and immunotherapy has emerged as a promising approach to increase the probability of abscopal effects, where distant tumors respond to treatment due to the systemic immunomodulatory effects. This review emphasizes the importance of GI in cancer biology and elucidates the mechanisms by which RT induces GI remodeling of the immune microenvironment. By elucidating the mechanisms of GI and RT-induced immune responses, we aim to emphasize the crucial importance of this approach in modern oncology. Understanding the impact of GI on tumor biological behavior and therapeutic response, as well as the possibility of activating systemic anti-tumor immunity through RT, will pave the way for the development of new treatment strategies and improve prognosis for patients.

Immune-related adverse events of antibody-based biological medicines in cancer therapy

Recombinant antibodies (Abs) are an integral modality for the treatment of multiple tumour malignancies. Since the Food and Drug Administration (FDA) approval of rituximab as the first monoclonal antibody (mAb) for cancer treatment, several mAbs and antibody (Ab)-based therapies have been approved for the treatment of solid tumour malignancies and other cancers. These Abs function by either blocking oncogenic pathways or angiogenesis, modulating immune response, or by delivering a conjugated drug. The use of Ab-based therapy in cancer patients who could benefit from the treatment, however, is still limited by associated toxicity profiles which may stem from biological features and processes related to target binding, alongside biochemical and/or biophysical characteristics of the therapeutic Ab. A significant immune-related adverse event (irAE) associated with Ab-based therapies is cytokine release syndrome (CRS), characterized by the development of fever, rash and even marked, life-threatening hypotension, and acute inflammation with secondary to systemic uncontrolled increase in a range of pro-inflammatory cytokines. Here, we review irAEs associated with specific classes of approved, Ab-based novel cancer immunotherapeutics, namely immune checkpoint (IC)-targeting Abs, bispecific Abs (BsAbs) and Ab-drug-conjugates (ADCs), highlighting the significance of harmonization in preclinical assay development for safety assessment of Ab-based biotherapeutics as an approach to support and refine clinical translation.

Unveiling the Impact of MRC1 on Immune Infiltration and Patient's Prognosis: A Pan-Cancer Analysis Based on Single-Cell and Bulk Sequencing

Purpose

Mannose receptor C-type 1 (MRC1) is an endocytic lectin receptor primarily expressed in macrophages, dendritic cells, and some endothelial cells. However, the role of MRC1 in cancers remains unclear.

Methods

We analyzed MRC1 expression using The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), and single-cell datasets. We systematically explored the prognostic implications and diagnostic value of MRC1. Immune-related indicators, including immune cells, immune scores, and immune checkpoint molecules, were used to estimate their correlation with MRC1 expression. Finally, we explored its potential ties to immunotherapy success markers such as tumor mutation burden and DNA repair genes.

Results

MRC1 showed both pro- and anti-tumor leanings depending on the cancer types. High levels correlated with poorer outcomes in six cancers but improved prognosis in some cancers like glioblastoma multiforme. This trend extended to the immune arena, where MRC1 intertwined with diverse immune parameters, suggesting its influence on affecting the tumor's immunological landscape. Intriguingly, its expression positively associated with factors favoring immunotherapy efficacy while negatively correlating with some potential barriers. Single-cell analysis pinpointed a specific link between MRC1 and DNA damage/repair pathways in breast cancer.

Conclusion

Our study provides a comprehensive landscape of MRC1 levels and diverse regulatory patterns in different cancers, deepening the understanding of MRC1's roles in tumorigenesis and immunity.

Predictive Impact of Tumor Mutational Burden on Real-World Outcomes of First-Line Immune Checkpoint Inhibition in Metastatic Melanoma

PURPOSE

The choice of threshold and reliability of high tumor mutational burden (TMB) to predict outcomes and guide treatment choice for patients with metastatic melanoma receiving first-line immune checkpoint inhibitor (ICI) therapy in the real world is not well known.

METHODS

Using a deidentified nationwide (US-based) melanoma clinicogenomic database, we identified a real-world cohort of patients with metastatic melanoma (N = 497) who received first-line monotherapy anti-PD-1 (n = 240) or dual anti-PD-1 and anti-CTLA-4 ICI (n = 257) and had a tissue-based comprehensive genomic profiling test TMB score.

RESULTS

TMB-high (TMB-H; ≥10 mutations per megabase [muts/Mb], n = 352, 71%) was independently predictive of superior real-world progression-free survival and overall survival versus TMB-low (<10 mut/Mb, n = 145, 29%) in both mono ICI (hazard ratio [HR], 0.45 [95% CI, 0.32 to 0.63]; P < .001; HR, 0.61 [95% CI, 0.41 to 0.90]; P = .01, respectively) and dual ICI (HR, 0.67 [95% CI, 0.49 to 0.90]; P = .009; HR, 0.61 [95% CI, 0.42 to 0.88]; P = .007, respectively) patients. Dual ICI offered no significant advantage in BRAFwt patients and unexpectedly demonstrated greatest benefit in the TMB 10-19 mut/Mb group, identifying a TMB-very high (≥20 mut/Mb, n = 247, 50%) BRAFmut patient subgroup for whom mono ICI may be preferable.

CONCLUSION

TMB-H predicts superior outcomes on ICI while coassessment of BRAF status and TMB may inform first-line regimen choice.

Identification of RFC4 as a potential biomarker for pan-cancer involving prognosis, tumour immune microenvironment and drugs

RFC4 is required for DNA polymerase δ and DNA polymerase ε to initiate DNA template expansion. Downregulated RFC4 inhibits tumour proliferation by causing S-phase arrest and inhibiting mitosis, resulting in the reduction of tumour cells. RFC4 has been implicated that it plays an important role in the initiation and progression of cancers, but a comprehensive analysis of the role of RFC4 in cancer has not been performed. We comprehensively analysed the expression, prognosis, methylation level, splicing level, relationship of RFC4 and immune infiltration, and pan-cancer immunotherapy response used various databases (including TCGA, GTEx, UALCAN, Oncosplicing, TIDE, TISCH, HPA and CAMOIP), and experimented its biological function in HCC. Through pan-cancer analysis, we found that RFC4 is significantly upregulated in most tumours. The tumour patients with high expression of RFC4 have poor prognosis. The methylation level and variable splicing level of RFC4 were abnormal in most tumours compared with the adjacent tissues. Furthermore, RFC4 was closely associated with immune cell infiltration in various cancers. RFC4 was significantly co-expressed with immune checkpoints and other immune-related genes. The expression of RFC4 could indicate the immunotherapy efficacy of some tumours. The RFC4 expression was associated with sensitivity to specific small molecule drugs. Cell experiments have shown that downregulated RFC4 can inhibit cell cycle and tumour cell proliferation. We conducted a systematic pan-cancer analysis of RFC4, and the results showed that RFC4 can serve as a biomarker for cancer diagnosis and prognosis. These findings open new perspectives for precision medicine.

Non-Small Cell Lung Cancer Metastatic Without Oncogenic Alterations

This overview provides a thorough review of current treatment approaches for first-line management of nononcogenic addicted non-small cell lung cancer. We also address pertinent clinical decision-making queries encountered in everyday practice, such as the optimal treatment strategy for PD-L1-high patients, predictive factors for response to immune checkpoint inhibitors (ICI) both in terms of patient and cancer characteristics, the potential benefits of dual checkpoint blockade, and the unresolved issue of safe discontinuation strategies for long-term responders. Around one in five patients falls into this latter category while the majority develop either primary or acquired resistance to ICI-based first-line therapy, necessitating effective subsequent lines of treatment. Docetaxel, with or without combination of antiangiogenic agents, serves as the backbone of treatment, although evidence in the post-ICI setting is limited. Given that an inflamed tumor microenvironment (TME) is crucial for ICI responses, targeting the TME in cases of acquired resistance alongside continued ICI administration appears rational, although clinical trials so far have failed to confirm this hypothesis. Antibody-drug conjugates have emerged as a promising treatment modality, offering the potential for reduced toxicity and improved efficacy by targeting specific cancer antigens. Moreover, several chemotherapy-free approaches are currently under investigation for treatment-naïve patients, including alternative ICI and drugs targeting epitopes on both cancer and immune cells.

Circulating biomarkers as predictors of response to immune checkpoint inhibitors in NSCLC: Are we on the right path?

Immune checkpoints inhibitors (ICIs) have markedly improved the therapeutic management of advanced NSCLC and, more recently, they have demonstrated efficacy also in the early-stage disease. Despite better survival outcomes with ICIs compared to standard chemotherapy, a large proportion of patients can derive limited clinical benefit from these agents. So far, few predictive biomarkers, including the programmed death-ligand 1 (PD-L1), have been introduced in clinical practice. Therefore, there is an urgent need to identify novel biomarkers to select patients for immunotherapy, to improve efficacy and avoid unnecessary toxicity. A deeper understanding of the mechanisms involved in antitumor immunity and advances in the field of liquid biopsy have led to the identification of a wide range of circulating biomarkers that could potentially predict response to immunotherapy. Herein, we provide an updated overview of these circulating biomarkers, focusing on emerging data from clinical studies and describing modern technologies used for their detection.

Differential Responses to Immune Checkpoint Inhibitors are Governed by Diverse Mismatch Repair Gene Alterations

PURPOSE

The response to immune checkpoint inhibitors (ICI) in deficient mismatch repair (dMMR) colorectal cancer and endometrial cancer is variable. Here, we explored the differential response to ICIs according to different mismatch repair alterations.

EXPERIMENTAL DESIGN

Colorectal cancer (N = 13,701) and endometrial cancer (N = 3,315) specimens were tested at Caris Life Sciences. Median overall survival (mOS) was estimated using Kaplan-Meier. The prediction of high-, intermediate-, and low-affinity epitopes by tumor mutation burden (TMB) values was conducted using R-squared (R2).

RESULTS

Compared with mutL (MLH1 and PMS2) co-loss, the mOS was longer in mutS (MSH2 and MSH6) co-loss in all colorectal cancer (54.6 vs. 36 months; P = 0.0.025) and endometrial cancer (81.5 vs. 48.2 months; P < 0.001) patients. In ICI-treated patients, the mOS was longer in mutS co-loss in colorectal cancer [not reached (NR) vs. 36 months; P = 0.011). In endometrial cancer, the mOS was NR vs. 42.2 months; P = 0.711]. The neoantigen load (NAL) in mutS co-loss compared with mutL co-loss was higher in colorectal cancer (high-affinity epitopes: 25.5 vs. 19; q = 0.017, intermediate: 39 vs. 32; q = 0.004, low: 87.5 vs. 73; q < 0.001) and endometrial cancer (high-affinity epitopes: 15 vs. 11; q = 0.002, intermediate: 27.5 vs. 19; q < 0.001, low: 59 vs. 41; q < 0.001), respectively. R2 ranged from 0.25 in mutS co-loss colorectal cancer to 0.95 in mutL co-loss endometrial cancer.

CONCLUSIONS

Patients with mutS co-loss experienced longer mOS in colorectal cancer and endometrial cancer and better response to ICIs in colorectal cancer. Among all explored biomarkers, NAL was higher in mutS co-loss and may be a potential driving factor for the observed better outcomes. TMB did not reliably predict NAL.

Treatment Options for Hepatocellular Carcinoma Using Immunotherapy: Present and Future

Hepatocellular carcinoma (HCC) is a common cancer, and the body's immune responses greatly affect its progression and the prognosis of patients. Immunological suppression and the maintenance of self-tolerance in the tumor microenvironment are essential responses, and these form part of the theoretical foundations of immunotherapy. In this review, we first discuss the tumor microenvironment of HCC, describe immunosuppression in HCC, and review the major biomarkers used to track HCC progression and response to treatment. We then examine antibody-based therapies, with a focus on immune checkpoint inhibitors (ICIs), monoclonal antibodies that target key proteins in the immune response (programmed cell death protein 1, anti-cytotoxic T-lymphocyte associated protein 4, and programmed death-ligand 1) which have transformed the treatment of HCC and other cancers. ICIs may be used alone or in conjunction with various targeted therapies for patients with advanced HCC who are receiving first-line treatments or subsequent treatments. We also discuss the use of different cellular immunotherapies, including T cell receptor (TCR) T cell therapy and chimeric antigen receptor (CAR) T cell therapy. We then review the use of HCC vaccines, adjuvant immunotherapy, and oncolytic virotherapy, and describe the goals of future research in the development of treatments for HCC.

Prognosis stratification of cancer patients treated with immune checkpoint inhibitors through lung immune prognostic index: a meta-analysis and systematic review

BACKGROUND

Although numerous studies have reported the prognostic value of the lung immune prognostic index (LIPI) in non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), the prognostic value of the LIPI in a pancancer setting remains unclear.

METHODS

A comprehensive search was conducted until July 2023 across the PubMed, Embase, Web of Science, and Cochrane Library databases to identify relevant studies evaluating the prognostic value of the LIPI in cancer patients treated with ICIs. The outcomes were overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and disease control rate (DCR). We described and compared the pooled outcomes by stratifying the patients based on different groupings of LIPI (good vs. intermediate [0 vs. 1], good vs. poor [0 vs. 2], and good vs. intermediate / poor [0 vs. 1 + 2]).

RESULTS

A total of 9959 patients in 35 studies were included. A higher score of LIPI was associated with impaired OS. The pooled HRs were 1.69 (95% CI: 1.55-1.85, p < 0.001; 0 vs. 1), 3.03 (95% CI: 2.53-3.63, p < 0.001; 0 vs. 2), and 2.38 (95% CI: 1.97-2.88, p < 0.001; 0 vs. 1 + 2). A higher LIPI score was associated with shorter PFS. The pooled HRs were 1.41 (95% CI: 1.31-1.52, p < 0.001; 0 vs. 1), 2.23 (95% CI: 1.87-2.66, p < 0.001; 0 vs. 2), and 1.65 (95% CI: 1.46-1.86, p < 0.001; 0 vs. 1 + 2). Similarly, a higher LIPI score was associated with a lower ORR. The pooled ORs were 0.63 (95% CI: 0.54-0.75, p < 0.001; 0 vs. 1) and 0.38 (95% CI: 0.29-0.50, p < 0.001; 0 vs. 2). A higher LIPI score was associated with a lower DCR. The pooled ORs were 0.47 (95% CI: 0.35-0.61, p < 0.001; 0 vs. 1) and 0.19 (95% CI: 0.12-0.30, p < 0.001; 0 vs. 2).

CONCLUSION

In patients with NSCLC or other solid tumours, the lung immune prognostic index could robustly stratify the clinical outcomes into three groups among the patients who receive ICIs. LIPI is a low-cost, simple, accessible, and accurate prognostic tool in a pancancer setting and it may contribute to the evaluation of risk stratification in patients treated with ICIs.

Understanding the Tumor Microenvironment in Melanoma Patients with In-Transit Metastases and Its Impacts on Immune Checkpoint Immunotherapy Responses

Melanoma is the leading cause of global skin cancer-related death and currently ranks as the third most commonly diagnosed cancer in Australia. Melanoma patients with in-transit metastases (ITM), a type of locoregional metastasis located close to the primary tumor site, exhibit a high likelihood of further disease progression and poor survival outcomes. Immunotherapies, particularly immune checkpoint inhibitors (ICI), have demonstrated remarkable efficacy in ITM patients with reduced occurrence of further metastases and prolonged survival. The major challenge of immunotherapeutic efficacy lies in the limited understanding of melanoma and ITM biology, hindering our ability to identify patients who likely respond to ICIs effectively. In this review, we provided an overview of melanoma and ITM disease. We outlined the key ICI therapies and the critical immune features associated with therapy response or resistance. Lastly, we dissected the underlying biological components, including the cellular compositions and their communication networks within the tumor compartment, to enhance our understanding of the interactions between immunotherapy and melanoma, providing insights for future investigation and the development of drug targets and predictive biomarkers.

The cell death-related genes machine learning model for precise therapy and clinical drug selection in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the prevailing subtype of hepatocellular malignancy. While previous investigations have evidenced a robust link with programmed cell death (PCD) and tumorigenesis, a comprehensive inquiry targeting the relationship between multiple PCDs and HCC remains scant. Our aim was to develop a predictive model for different PCD patterns in order to investigate their impact on survival rates, prognosis and drug response rates in HCC patients. We performed functional annotation and pathway analysis on identified PCD-related genes (PCDRGs) using multiple bioinformatics tools. The prognostic value of these PCDRGs was verified through a dataset obtained from GEO. Consensus clustering analysis was utilized to elucidate the correlation between diverse PCD clusters and pertinent clinical characteristics. To comprehensively uncover the distinct PCD regulatory patterns, our analysis integrated gene expression profiling, immune cell infiltration and enrichment analysis. To predict survival differences in HCC patients, we established a PCD model. To enhance the clinical applicability for the model, we developed a highly accurate nomogram. To address the treatment of HCC, we identified several promising chemotherapeutic agents and novel targeted drugs. These drugs may be effective in treating HCC and could improve patient outcomes. To develop a cell death feature for HCC patients, we conducted an analysis of 12 different PCD mechanisms using eligible data obtained from public databases. Through this analysis, we were able to identify 1254 PCDRGs likely to contribute to cell death on HCC. Further analysis of 1254 PCDRGs identified 37 genes with prognostic value in HCC patients. These genes were then categorized into two PCD clusters A and B. The categorization was based on the expression patterns of the genes in the different clusters. Patients in PCD cluster B had better survival probabilities. This suggests that PCD mechanisms, as represented by the genes in cluster B, may have a protective effect against HCC progression. Furthermore, the expression of PCDRGs was significantly higher in PCD cluster A, indicating that this cluster may be more closely associated with PCD mechanisms. Furthermore, our observations indicate that patients exhibiting elevated tumour mutation burden (TMB) are at an augmented risk of mortality, in comparison to those displaying low TMB and low-risk statuses, who are more likely to experience prolonged survival. In addition, we have investigated the potential distinctions in the susceptibility of diverse risk cohorts towards emerging targeted therapies, designed for the treatment of HCC. Moreover, our investigation has shown that AZD2014, SB505124, LJI308 and OSI-207 show a greater efficacy in patients in the low-risk category. Conversely, for the high-risk group patients, PD173074, ZM447439 and CZC24832 exhibit a stronger response. Our findings suggest that the identification of risk groups and personalized treatment selection could lead to better clinical outcomes for patients with HCC. Furthermore, significant heterogeneity in clinical response to ICI therapy was observed among HCC patients with varying PCD expression patterns. This novel discovery underscores the prospective usefulness of these expression patterns as prognostic indicators for HCC patients and may aid in tailoring targeted treatment for those of distinct risk strata. Our investigation introduces a novel prognostic model for HCC that integrates diverse PCD expression patterns. This innovative model provides a novel approach for forecasting prognosis and assessing drug sensitivity in HCC patients, driving a more personalized and efficacious treatment paradigm, elevating clinical outcomes. Nonetheless, additional research endeavours are required to confirm the model's precision and assess its potential to inform clinical decision-making for HCC patients.

Current and emerging sequencing-based tools for precision cancer medicine

Current precision cancer medicine is dependent on the analyses of a plethora of clinically relevant genomic aberrations. During the last decade, next-generation sequencing (NGS) has gradually replaced most other methods for precision cancer diagnostics, spanning from targeted tumor-informed assays and gene panel sequencing to global whole-genome and whole-transcriptome sequencing analyses. The shift has been impelled by a clinical need to assess an increasing number of genomic alterations with diagnostic, prognostic and predictive impact, including more complex biomarkers (e.g. microsatellite instability, MSI, and homologous recombination deficiency, HRD), driven by the parallel development of novel targeted therapies and enabled by the rapid reduction in sequencing costs. This review focuses on these sequencing-based methods, puts their emergence in a historic perspective, highlights their clinical utility in diagnostics and decision-making in pediatric and adult cancer, as well as raises challenges for their clinical implementation. Finally, the importance of applying sensitive tools for longitudinal monitoring of treatment response and detection of measurable residual disease, as well as future avenues in the rapidly evolving field of sequencing-based methods are discussed.

Integrative analysis of bulk and single-cell RNA-seq reveals the molecular characterization of the immune microenvironment and oxidative stress signature in melanoma

Background

The immune microenvironment and oxidative stress of melanoma show significant heterogeneity, which affects tumor growth, invasion and treatment response. Single-cell and bulk RNA-seq data were used to explore the heterogeneity of the immune microenvironment and oxidative stress of melanoma.

Methods

The R package Seurat facilitated the analysis of the single-cell dataset, while Harmony, another R package, was employed for batch effect correction. Cell types were classified using Uniform Manifold Approximation and Projection (UMAP). The Secreted Signaling algorithm from CellChatDB.human was applied to elucidate cell-to-cell communication patterns within the single-cell data. Consensus clustering analysis for the skin cutaneous melanoma (SKCM) samples was executed with the R package ConsensusClusterPlus. To quantify immune infiltrating cells, we utilized CIBERSORT, ESTIMATE, and TIMERxCell algorithms provided by the R package Immuno-Oncology Biological Research (IOBR). Single nucleotide variant (SNV) analysis was conducted using Maftools, an R package specifically designed for this purpose. Subsequently, the expression levels of PXDN and PAPSS2 genes were assessed in melanoma tissues compared to adjacent normal tissues. Furthermore, in vitro experiments were conducted to evaluate the proliferation and reactive oxygen species expression in melanoma cells following transfection with siRNA targeting PXDN and PAPSS2.

Results

Malignant tumor cell populations were reclassified based on a comprehensive single-cell dataset analysis, which yielded six distinct tumor subsets. The specific marker genes identified for these subgroups were then used to interrogate the Cancer Genome Atlas Skin Cutaneous Melanoma (TCGA-SKCM) cohort, derived from bulk RNA sequencing data, resulting in the delineation of two immune molecular subtypes. Notably, patients within the cluster2 (C2) subtype exhibited a significantly more favorable prognosis compared to those in the cluster1 (C1) subtype. An alignment of immune characteristics was observed between the C2 subtype and unique immune functional tumor cell subsets. Genes differentially expressed across these subtypes were subsequently leveraged to construct a predictive risk model. In vitro investigations further revealed elevated expression levels of PXDN and PAPSS2 in melanoma tissue samples. Functional assays indicated that modulation of PXDN and PAPSS2 expression could influence the production of reactive oxygen species (ROS) and the proliferative capacity of melanoma cells.

Conclusion

The constructed six-gene signature can be used as an immune response and an oxidative stress marker to guide the clinical diagnosis and treatment of melanoma.

Phase II study of nivolumab in patients with genetic alterations in DNA damage repair and response who progressed after standard treatment for metastatic solid cancers (KM-06)

BACKGROUND

Immune-modulating antibodies targeting programmed cell death protein 1/programmed death-ligand 1 (PD-1/PD-L1) have demonstrated promising antitumor efficacy in various types of cancers, especially highly mutated ones. Genetic alterations in DNA damage response and repair (DDR) genes can lead to genetic instability, often accompanied by a high tumor mutation burden (TMB). However, few studies have validated the aberration of DDR genes as a predictive biomarker for response to immune-modulating antibodies.

METHODS

The KM-06 open-label, multicenter, single-arm, phase II trial evaluated the safety and efficacy of nivolumab in refractory solid cancers with DDR gene mutations assessed by clinically targeted sequencing. Nivolumab (3 mg/kg) was administered every 2 weeks until disease progression, unacceptable toxicity, or for 24 months. The primary endpoint was the objective response rate (ORR) as per RECIST V.1.1 criteria.

RESULTS

A total of 48 patients were enrolled in the study (median age 61, 58.3% male). The most common cancer type was colorectal cancer (41.7%), followed by prostate and biliary tract cancer (8.3% each). Eight patients achieved a partial response as their best overall response, resulting in an ORR of 17.8%. The disease control rate was 60.0%. The median progression-free survival was 2.9 months. Treatment-related adverse events of any grade and grade ≥3 occurred in 44 (91.7%) and 4 (8.3%) patients, respectively. Clinically targeted sequencing data inferred both TMB and microsatellite instability (MSI). Using a TMB cut-off of 12 mut/Mb, there were significant differences in overall survival (p=0.00035), progression-free survival (p=0.0061), and the best overall response (p=0.05). In the RNA sequencing analysis, nivolumab responders showed activation of the interleukin signaling pathway. Patients who experienced early progression presented high epithelial-mesenchymal transition signaling pathway activation. The responders exhibited a marked increase in PD-1-/Ki67+CD8 T cells at the early stage of treatment (C3D1) compared with non-responders (p=0.03).

CONCLUSIONS

In this phase II trial, nivolumab demonstrated moderate efficacy and manageable toxicity in patients with solid cancer harboring DDR gene mutations. A high TMB (>12 mut/Mb) and MSI score (>2.5) determined through clinically target sequencing presented significant discriminatory power for the nivolumab response.

TRIAL REGISTRATION NUMBER

NCT04761744.

Novel prognostic signature for lung adenocarcinoma based on immune-related mRNA pairs

Lung adenocarcinoma (LUAD) is a highly lethal malignant tumor. While the involvement of multiple mRNAs in the progression of LUAD is well established, the potential diagnostic value of immune-related mRNAs (irmRNAs) in LUAD remains largely unexplored. In this study, we utilized RNA-seq, clinical data, and immune-related gene information from LUAD patients to identify differentially expressed immune-related mRNAs (DEirmRNAs) and developed a predictive risk model based on specific DEirmRNA pairs closely linked with patient prognosis. We classified patients into high-risk and low-risk groups and analyzed factors such as survival rate, clinical characteristics, gene enrichment, immune cell infiltration, tumor mutation load, and drug susceptibility. We confirmed the expression levels of these DEirmRNAs in tumor tissues using qRT-PCR assay. Our results showed that the low-risk group had a longer survival time and lower tumor mutation burden (TMB) and microsatellite instability (MSI) compared to the high-risk group. The high-risk group also had a significant reduction in the number of certain immune cells and a lower half-maximum inhibitor concentration (IC50). We identified specific DEirmRNA pairs that were up-regulated or down-regulated in tumor tissues compared to adjacent tissues. Our prognostic risk model based on DEirmRNA pairs could be used to predict the prognosis of LUAD patients and provide reference for better treatment.

Analytical validation and clinical utilization of K-4CARE™: a comprehensive genomic profiling assay with personalized MRD detection

Background: Biomarker testing has gradually become standard of care in precision oncology to help physicians select optimal treatment for patients. Compared to single-gene or small gene panel testing, comprehensive genomic profiling (CGP) has emerged as a more time- and tissue-efficient method. This study demonstrated in-depth analytical validation of K-4CARE, a CGP assay that integrates circulating tumor DNA (ctDNA) tracking for residual cancer surveillance. Methods: The assay utilized a panel of 473 cancer-relevant genes with a total length of 1.7 Mb. Reference standards were used to evaluate limit of detection (LOD), concordance, sensitivity, specificity and precision of the assay to detect single nucleotide variants (SNVs), small insertion/deletions (Indels), gene amplification and fusion, microsatellite instability (MSI) and tumor mutational burden (TMB). The assay was then benchmarked against orthogonal methods using 155 clinical samples from 10 cancer types. In selected cancers, top tumor-derived somatic mutations, as ranked by our proprietary algorithm, were used to detect ctDNA in the plasma. Results: For detection of somatic SNVs and Indels, gene fusion and amplification, the assay had sensitivity of >99%, 94% and >99% respectively, and specificity of >99%. Detection of germline variants also achieved sensitivity and specificity of >99%. For TMB measurement, the correlation coefficient between whole-exome sequencing and our targeted panel was 97%. MSI analysis when benchmarked against polymerase chain reaction method showed sensitivity of 94% and specificity of >99%. The concordance between our assay and the TruSight Oncology 500 assay for detection of somatic variants, TMB and MSI measurement was 100%, 89%, and 98% respectively. When CGP-informed mutations were used to personalize ctDNA tracking, the detection rate of ctDNA in liquid biopsy was 79%, and clinical utility in cancer surveillance was demonstrated in 2 case studies. Conclusion: K-4CARE™ assay provides comprehensive and reliable genomic information that fulfills all guideline-based biomarker testing for both targeted therapy and immunotherapy. Integration of ctDNA tracking helps clinicians to further monitor treatment response and ultimately provide well-rounded care to cancer patients.

Genomic discordances and heterogeneous mutational burden, PD-L1 expression and immune infiltrates of non-small cell lung cancer metastasis

AIMS

To investigate the genomic discordances and heterogeneous mutational burden, PD-L1 expression and immune cell (IC) infiltrates of non-small cell lung cancer (NSCLC) metastasis.

METHODS

Surgical samples from 41 cases of NSCLC with metastatic tumours (MTs) and paired primary tumours (PTs) were collected. PD-L1 expression and ICs were quantified using image-based immunohistochemistry profiling. Whole exome sequencing was employed to explore discrepancies in genomic characteristics, tumour mutational burden (TMB) and tumour neoantigen burden (TNB) in 28 cases.

RESULTS

Non-synonymous mutations in MTs were slightly more than in PTs, with only 42.34% of mutations shared between paired PTs and MTs. The heterogeneity of TMB showed no significant difference (p=0.785) between MTs and PTs, while TNB significantly increased in MTs (p=0.013). MTs generally exhibited a higher density of PD-L1+ cells and a higher tumour proportion score with a lower density of IC infiltrates. Subgroup analysis considering clinicopathological factors revealed that the heterogeneity of immune biomarkers was closely associated with the histology of lung adenocarcinoma, metastatic sites of extrapulmonary, time intervals and treatment history. Prognosis analysis indicated that a high density of CD8+ T cells was a low-risk factor, whereas a high density of PD-L1+ cells in MTs was a high-risk factor for cancer-related death in metastatic NSCLC.

CONCLUSIONS

The mutational burden, PD-L1 expression and IC infiltrates undergo changes during NSCLC metastasis, which may impact the immunotherapeutic benefits in patients with NSCLC with metastatic progression and should be monitored according to clinical scenarios.

Tumor immunotherapy resistance: Revealing the mechanism of PD-1 / PD-L1-mediated tumor immune escape

Tumor immunotherapy, an innovative anti-cancer therapy, has showcased encouraging outcomes across diverse tumor types. Among these, the PD-1/PD-L1 signaling pathway is a well-known immunological checkpoint, which is significant in the regulation of immune evasion by tumors. Nevertheless, a considerable number of patients develop resistance to anti-PD-1/PD-L1 immunotherapy, rendering it ineffective in the long run. This research focuses on exploring the factors of PD-1/PD-L1-mediated resistance in tumor immunotherapy. Initially, the PD-1/PD-L1 pathway is characterized by its role in facilitating tumor immune evasion, emphasizing its role in autoimmune homeostasis. Next, the primary mechanisms of resistance to PD-1/PD-L1-based immunotherapy are analyzed, including tumor antigen deletion, T cell dysfunction, increased immunosuppressive cells, and alterations in the expression of PD-L1 within tumor cells. The possible ramifications of altered metabolism, microbiota, and DNA methylation on resistance is also described. Finally, possible resolution strategies for dealing with anti-PD-1/PD-L1 immunotherapy resistance are discussed, placing particular emphasis on personalized therapeutic approaches and the exploration of more potent immunotherapy regimens.

Refining PD-1/PD-L1 assessment for biomarker-guided immunotherapy: A review

Anti-programmed cell death ligand 1 (anti-PD-L1)  immunotherapy is an increasingly crucial in cancer treatment. To date, the Federal Drug Administration (FDA) has approved four PD-L1 immunohistochemistry (IHC) staining protocols, commercially available in the form of "kits", facilitating testing for PD-L1 expression. These kits comprise four PD-L1 antibodies on two separate IHC platforms, each utilizing distinct, non-interchangeable scoring systems. Several factors, including tumor heterogeneity and the size of the tissue specimens assessed, can lead to PD-L1 status misclassification, potentially hindering the initiation of therapy. Therefore, the development of more accurate predictive biomarkers to distinguish between responders and non-responders prior to anti-PD-1/PD-L1 therapy warrants further research. Achieving this goal necessitates refining sampling criteria, enhancing current methods of PD-L1 detection, and deepening our understanding of the impact of additional biomarkers. In this article, we review potential solutions to improve the predictive accuracy of PD-L1 assessment in order to more precisely anticipate patients' responses to anti-PD-1/PD-L1 therapy, monitor disease progression and predict clinical outcomes.

Identifying survival of pan-cancer patients under immunotherapy using genomic mutation signature with large sample cohorts

Although immune checkpoint inhibitors have led to durable clinical response in multiple cancers, only a small proportion of patients respond to this treatment. Therefore, we aim to develop a predictive model that utilizes gene mutation profiles to accurately identify the survival of pan-cancer patients with immunotherapy. Here, we develop and evaluate three different nomograms using two cohorts containing 1,594 cancer patients whose mutation profiles are obtained by MSK-IMPACT sequencing and 230 cancer patients receiving whole-exome sequencing, respectively. Using eighteen genes (SETD2, BRAF, NCOA3, LATS1, IL7R, CREBBP, TET1, EPHA7, KDM5C, MET, KMT2D, RET, PAK7, CSF1R, JAK2, FAT1, ASXL1 and SPEN), the first nomogram stratifies patients from both cohorts into High-Risk and Low-Risk groups. Pan-cancer patients in the High-Risk group exhibit significantly shorter overall survival and progression-free survival than patients in the Low-Risk group in both cohorts. Meanwhile, the first nomogram also accurately identifies the survival of patients with melanoma or lung cancer undergoing immunotherapy, or pan-cancer patients treated with anti-PD-1/PD-L1 inhibitor or anti-CTLA-4 inhibitor. The model proposed is not a prognostic model for the survival of pan-cancer patients without immunotherapy, but a simple, effective and robust predictive model for pan-cancer patients' survival under immunotherapy, and could provide valuable assistance for clinical practice.

The co-inhibitory immune checkpoint proteins B7-H1(PD-L1) and B7-H4 in high grade glioma: From bench to bedside

Co-inhibitory immune checkpoints play a crucial role in tumor progression, and PD-1/PD-L1 inhibitor has been a breakthrough for treating multiple refractory tumors in last decade. Nevertheless, results of several phase III clinical trials of PD-1/PD-L1 inhibitor are unsatisfactory in high grade gliomas recently. This article reviews the promising biomarkers which can predict the efficacy of PD-1/PD-L1 blockade immunotherapy and current status of emerging strategies involving PD-1/PD-L1 inhibitors, especially the combination treatment and neoadjuvant PD-1 therapy in gliomas. In addition, B7-H4, one of the most promising immune checkpoints, is also briefly reviewed here for its clinical significance, regulatory mechanism and developing immunotherapeutic strategies in pre-clinical glioma models.

Circulating Immune Proteins: Improving the Diagnosis and Clinical Outcome in Advanced Non-Small Cell Lung Cancer

Immunotherapy has been proven a viable treatment option for non-small cell lung cancer (NSCLC) treatment in patients. However, some patients still do not benefit. Finding new predictive biomarkers for immunocheckpoint inhibitor (ICI) response will improve treatment management in the clinical routine. In this regard, liquid biopsy is a useful and noninvasive alternative to surgical biopsies. In the present study, we evaluated the potential diagnostic, prognostic, and predictive value of seven different soluble mediators involved in immunoregulation. Fifty-two plasma samples from advanced NSCLC treated in first-line with pembrolizumab at baseline (PRE) and at first response assessment (FR) were analyzed. In terms of diagnostic value, our results revealed that sFGL1, sGAL-3, and sGAL-1 allowed for optimal diagnostic efficacy for cancer patients. Additionally, the combination of sFGL1 and sGAL-3 significantly improved diagnostic accuracy. Regarding the predictive value to assess patients' immune response, sCD276 levels at PRE were significantly higher in patients without tumor response (p = 0.035). Moreover, we observed that high levels of sMICB at PRE were associated with absence of clinical benefit (pembrolizumab treatment less than 6 months) (p = 0.049), and high levels of sMICB and sGAL-3 at FR are also related to a lack of clinical benefit (p = 0.027 and p = 0.03, respectively). Finally, in relation to prognosis significance, at PRE and FR, sMICB levels above the 75th percentile are related to poor progression-free survival (PFS) (p = 0.013 and p = 0.023, respectively) and overall survival (OS) (p = 0.001 and p = 0.011, respectively). An increase in sGAL3 levels at FR was associated with worse PFS (p = 0.037). Interestingly, high sGAL-3 at PRE was independently associated with PFS and OS with a hazard ratio (HR) of 2.45 (95% CI 1.14-5.25; p = 0.021) and 4.915 (95% CI 1.89-12.73; p = 0.001). In conclusion, plasma levels of sFGL1, sGAL-3, and sGAL-1 could serve as diagnostic indicators and sMICB, sCD276, and sGAL3 were linked to outcomes, suggesting their potential in assessing NSCLC under pembrolizumab treatment. Our results highlight the value of employing soluble immune biomarkers in advanced lung cancer patients treated with pembrolizumab at first-line.

Assessing the Phenotype of a Homologous Recombination Deficiency Using High Resolution Array-Based Comparative Genome Hybridization in Ovarian Cancer

Ovarian cancer (OC) cells with homologous recombination deficiency (HRD) accumulate genomic scars (LST, TAI, and LOH) over a value of 42 in sum. PARP inhibitors can treat OC with HRD. The detection of HRD can be done directly by imaging these genomic scars, or indirectly by detecting mutations in the genes involved in HR. We show that HRD detection is also possible using high-resolution aCGH. A total of 30 OCs were analyzed retrospectively with high-resolution arrays as a test set and 19 OCs prospectively as a validation set. Mutation analysis was performed by HBOC TruRisk V2 panel to detect HR-relevant mutations. CNVs were clustered with respect to the involved HR genes versus the OC cases. In prospective validation, the HRD status determined by aCGH was compared with external HRD assessments. Two BRCA mutation carriers did not have HRD. OC could approximately differentiate into two groups with characteristic CNV patterns with different survival rates. Mutation frequencies have a linear regression on the HRD score. Mutations in individual HR-relevant genes do not always indicate HRD. This may depend on the mutation frequency in tumor cells. The aCGH shows the genomic scars of an HRD inexpensively and directly.

The Efficacy of Immunotherapy and Clinical Utility of Comprehensive Genomic Profiling in Adenoid Cystic Carcinoma of Head and Neck

Background and Objectives: Adenoid cystic carcinoma (ACC) of the head and neck is generally slow-growing but has a high potential for local recurrence and metastasis to distant organs. There is currently no standard pharmacological treatment for recurrent/metastatic (R/M) ACC, and there are cases in which immune checkpoint inhibitors (ICIs) are administered for ACC according to head and neck squamous cell carcinoma (HNSCC). However, the efficacy of ICIs for ACC remains unclear, and the predictive biomarkers need to be elucidated. Materials and Methods: The Center for Cancer Genomics and Advanced Therapeutics (C-CAT) database enabled the retrospective but nationwide analysis of 263 cases of ACC of the head and neck. Then, we examined and reported four cases of ACC that received ICIs and comprehensive genomic profiling (CGP) in our institution. Results: The C-CAT database revealed that 59 cases out of 263 received ICIs, and the best response was 8% of objective response rate (ORR) and 53% of disease control rate (DCR) (complete response, CR 3%, partial response, PR 5%, stable disease, SD 44%, progressive disease, PD 19%, not evaluated, NE 29%). The tumor mutational burden (TMB) in ACC was lower overall compared to HNSCC and could not be useful in predicting the efficacy of ICIs. Some cases with MYB structural variants showed the response to ICIs in the C-CAT database. A patient with MYB fusion/rearrangement variants in our institution showed long-term stable disease. Conclusions: ICI therapy is a potential treatment option, and the MYB structural variant might be a candidate for predictive biomarkers for immunotherapy in patients with R/M ACC.

Genetic landscape and PD-L1 expression in Epstein-Barr virus-associated gastric cancer according to the histological pattern

Epstein-Barr virus (EBV)-associated gastric cancer (EBVaGC) is a distinct molecular subtype of gastric cancer. This study aims to investigate genomic and clinicopathological characteristics of EBVaGC according to the histological pattern. We retrospectively collected 18 specimens of surgically resected EBVaGCs. Whole-exome sequencing was performed for all cases. Moreover, PD-L1 expression and tumor-infiltrating lymphocyte (TIL) percentage were investigated. Among 18 EBVaGCs, 10 cases were of intestinal histology, 3 were of poorly cohesive histology, and the remaining 5 were of gastric carcinoma with lymphoid stroma histology. Whole-exome sequencing revealed that EBVaGCs with intestinal histology harbored pathogenic mutations known to frequently occur in tubular or papillary adenocarcinoma, including TP53, KRAS, FBXW7, MUC6, ERBB2, CTNNB1, and ERBB2 amplifications. One patient with poorly cohesive carcinoma histology harbored a CDH1 mutation. Patients with EBVaGCs with intestinal or poorly cohesive carcinoma histology frequently harbored driver mutations other than PIK3CA, whereas those with EBVaGCs with gastric carcinoma with lymphoid stroma histology lacked other driver mutations. Moreover, the histological pattern of EBVaGCs was significantly associated with the levels of TILs (P = 0.005) and combined positive score (P = 0.027). In conclusion, patients with EBVaGCs with different histological patterns exhibited distinct genetic alteration, PD-L1 expression, and degree of TILs.

A Method for Extending Target Regions of Genomic Profiling by Combining a Custom Probe Pool with a Commercial Targeted Panel

BACKGROUND

Next-generation sequencing (NGS)-based genomic profiling is becoming widespread in determining treatment policies for patients with tumors. Commercially available gene panels for pan-tumor targets comprise hundreds of tumor-related genes but frequently lack genes of interest in specific tumor types. In this study, we demonstrate a method for extending target regions of genomic profiling by combining a custom probe pool with a commercial targeted panel.

METHODS

We used TruSight Oncology 500 (TSO500) as a commercial targeted panel and a custom probe pool designed for all exons of the SMARCA2 gene. Sequencing libraries of custom targets were constructed using a portion of the TSO500 library solution before the hybridization-capture process. After hybridization capture, both libraries were combined and sequenced using a next-generation sequencer.

RESULTS

Sequencing results showed that >96.8% and 100% of the target exons were covered at a depth of over 100× using the TSO500 and custom panels, respectively. The custom panels had slightly better median exon coverage than the TSO500. The combined libraries of the custom and TSO500 panels showed a mapped read ratio close to the mixing ratio. Analysis of mutation-free regions showed similar accuracies between the TSO500 and custom panels regarding variant calling.

CONCLUSIONS

Our devised method easily and affordably extends the targets beyond a ready-made panel. This method provides a valuable solution until the widespread adoption of whole-exome sequencing, which is costly for large target sizes.

Immunocheckpoint Inhibitors in Microsatellite-Stable or Proficient Mismatch Repair Metastatic Colorectal Cancer: Are We Entering a New Era?

Colorectal cancer (CRC) is the third most frequent cancer and the second leading cause of cancer-related deaths in Europe. About 5% of metastatic CRC (mCRC) are characterized by high microsatellite instability (MSI) due to a deficient DNA mismatch repair (dMMR), and this condition has been related to a high sensitivity to immunotherapy, in particular to the Immune Checkpoint Inhibitors (ICIs). In fact, in MSI-H or dMMR mCRC, treatment with ICIs induced remarkable response rates and prolonged survival. However, the majority of mCRC cases are mismatch-repair-proficient (pMMR) and microsatellite-stable (MSS), and unfortunately these conditions involve resistance to ICIs. This review aims to provide an overview of the strategies implemented to overcome ICI resistance and/or define subgroups of patients with MSS or dMMR mCRC who may benefit from immunotherapy.

Development and validation of a novel anoikis-related gene signature in clear cell renal cell carcinoma

Background

Despite numerous treatments available, clear cell renal cell carcinoma (ccRCC) remains a deadly and invasive cancer. Anoikis-related genes (ARGs) are essential regulators of tumor metastasis and development. However, the potential roles of ARGs in ccRCC remain unclear.

Methods

Based on the TCGA-KIRC cohort and GeneCards database, we identified differentially expressed ARGs in ccRCC. Then a 4 ARGs risk model was created by Cox regression and LASSO. The Kaplan-Meier and receiver operating characteristic (ROC) curves were utilized to verify the predictive efficacy of the prognostic signature. Subsequently, the possible molecular mechanism of ARGs was investigated by functional enrichment analysis. To assess the immune infiltration, immune checkpoint genes, and immune function in various risk groups, single sample gene set enrichment (ssGSEA) algorithm was employed. Furthermore, the low-risk and high-risk groups were compared in terms of tumor mutation burden (TMB). Ultimately, we analyzed the protein expression of these four ARGs utilizing the western blot test.

Results

Four genes were utilized to create a risk signature that may predict prognosis, enabling the classification of KIRC patients into groups with low or high risk. The reliability of the signature was examined utilizing survival analysis and ROC analysis. According to the multivariate Cox regression result, the risk score was a reliable independent prognostic predictor for KIRC patients. The novel risk model could differentiate between KIRC patients with various clinical outcomes and represent KIRC's specific immune status. An analysis of the correlation of TMB and risk score indicated a positive correlation between them, with high TMB being potentially linked to worse outcomes.

Conclusion

Based on our findings, the prognostic signature of ARGs may be employed as an independent prognostic factor for ccRCC patients. It may introduce alternative perspectives on prognosis evaluation and serve as a prominent reference for personalized and precise therapy in KIRC.

Spatial heterogeneity of T cell repertoire across NSCLC tumors, tumor edges, adjacent and distant lung tissues

Background

A better understanding of T cells in lung cancer and their distribution across tumor-adjacent lungs and peripheral blood is needed to improve efficacy and minimize toxicity from immunotherapy to lung cancer patients.

Methods

Here, we performed CDR3β TCR sequencing of 136 samples from 20 patients with early-stage NSCLC including peripheral blood mononuclear cells, tumors, tumor edges (<1 cm from tumor), as well as adjacent lungs 1 cm, 2 cm, 5 cm, and 10 cm away from the tumor to gain insight into the spatial heterogeneity of T cells across the lungs in patients with NSCLC. PD-L1, CD4, and CD8 expression was assessed using immunohistochemical staining, and genomic features were derived by targeted sequencing of 1,021 cancer-related genes. Multiplex immunohistochemistry against PD-1, CTLA4, LAG3, and TIM3 was performed on four patients to assess T cell exhaustion.

Results

Our study reveals a decreasing gradient in TIL Tumor Infiltrating Lymphocytes homology with tumor edge, adjacent lungs, and peripheral blood but no discernible distance-associated patterns of T cell trafficking within the adjacent lung itself. Furthermore, we show a decrease in pathogen-specific TCRs in regions with high T cell clonality and PD-L1 expression.

Conclusions

Exclusion in T exhaustion cells at play across the lungs of patients with NSCLC may potentially be the mechanism for lung cancer occurrence.

Clinical implications of RAB13 expression in pan-cancer based on multi-databases integrative analysis

Worldwide, cancer is a huge burden, and each year sees an increase in its incidence. RAB (Ras-related in brain) 13 is crucial for a number of tumor types. But more research on RAB13's tumor-related mechanism is still required. This study's goal was to investigate RAB13's function in human pan-cancer, and we have also preliminarily explored the relevant mechanisms. To investigate the differential expression, survival prognosis, immunological checkpoints, and pathological stage of RAB13 in human pan-cancer, respectively, databases of TIMER2.0, GEPIA 2, and UALCAN were employed. CBioPortal database was used to analyze the mutation level, meanwhile, PPI network was constructed based on STRING website. The putative functions of RAB13 in immunological infiltration were investigated using single sample gene set enrichment analysis (ssGSEA). The mechanism of RAB13 in hepatocellular cancer was also briefly investigated by us using gene set enrichment analysis (GSEA). RAB13 was differentially expressed in a number of different cancers, including liver hepatocellular carcinoma (LIHC), stomach adenocarcinoma (STAD), etc. Additionally, RAB13 overexpression in LGG and LIHC is associated with a worse prognosis, including overall survival (OS) and disease-free survival (DFS). Then, we observed that early in BLCA, BRAC, CHOL, ESCA, HNSC, KICH, KIRC, LIHC, LUAD, LUSC, and STAD, the level of RAB13 expression was raised. Next, we found that "amplification" was the most common mutation in RAB13. The expression of SLC39A1, JTB, SSR2, SNAPIN, and RHOC was strongly positively linked with RAB13, according to a correlation study. RAB13 favorably regulated B cell, CD8 + T cell, CD4 + T cell, macrophage, neutrophil, and dendritic cell in LIHC, according to immune infiltration analysis. Immune checkpoint study revealed a positive correlation between RAB13 expression and PD1, PDL1, and CTLA4 in LIHC. According to GSEA, RAB13 is involved in a number of processes in LIHC, including MTORC1 signaling, MYC targets v1, G2M checkpoint, MITOTIC spindle, DNA repair, P53 pathway, glycolysis, PI3K-AKT-MTOR signaling, etc. RAB13 is a possible therapeutic target in LIHC and can be used as a prognostic marker.

Unraveling molecular networks in thymic epithelial tumors: deciphering the unique signatures

Thymic epithelial tumors (TETs) are a rare and diverse group of neoplasms characterized by distinct molecular signatures. This review delves into the complex molecular networks of TETs, highlighting key aspects such as chromosomal abnormalities, molecular subtypes, aberrant gene mutations and expressions, structural gene rearrangements, and epigenetic changes. Additionally, the influence of the dynamic tumor microenvironment on TET behavior and therapeutic responses is examined. A thorough understanding of these facets elucidates TET pathogenesis, offering avenues for enhancing diagnostic accuracy, refining prognostic assessments, and tailoring targeted therapeutic strategies. Our review underscores the importance of deciphering TETs' unique molecular signatures to advance personalized treatment paradigms and improve patient outcomes. We also discuss future research directions and anticipated challenges in this intriguing field.

Integrating angiogenesis signature and tumor mutation burden for improved patient stratification in immune checkpoint blockade therapy for muscle-invasive bladder cancer

BACKGROUND

Muscle-invasive bladder cancer (MIBC) patients have benefitted greatly from immune checkpoint blockade (ICB) therapy. However, there is a pressing need to identify factors underlying the heterogeneity of clinical responses to ICB.

METHODS

We conducted a study on 848 MIBC patients from 4 independent cohorts to investigate the key biological characteristics affecting ICB responses. The IMvigor210 cohort (n = 234) was used to identify the key factor, followed by exploration of the correlation between tumor angiogenesis and immune suppression in the IMvigor210, TCGA (n = 391), and UNC-108 (n = 89) cohorts. The ZSHS cohort (n = 134) was used for validation. Additionally, we integrated angiogenesis signature with tumor mutation burden (TMB) to decipher the heterogeneity of clinical outcomes to ICB in MIBC patients.

RESULTS

Our analysis revealed that nonresponders to PD-L1 blockade were enriched with angiogenesis signature. Furthermore, we observed a correlation between angiogenesis signature and decreased neoantigen load, downregulated T-cell antigen recognition, and noninflamed immunophenotype. We identified a subgroup of patients resistant to ICB, characterized by high angiogenesis signature and low tumor mutation burden (TMB), and found the activation of TGF-β signaling and downregulation of T-cell cytolytic signatures in this subgroup.

CONCLUSIONS

The study concluded that angiogenesis signature is closely associated with an immunosuppressive microenvironment, leading to resistance to ICB therapy in MIBC patients. The study further suggested that the combination of angiogenesis signature and TMB can serve as an integrated biomarker for better stratification of patients' clinical outcomes to ICB therapy.

Understanding the Impact of Population and Cancer Type on Tumor Mutation Burden Scores: A Comprehensive Whole-Exome Study in Cancer Patients From India

PURPOSE

The purpose of this study was to understand the impact of population diversity and geographic variation on tumor mutation burden (TMB) scores across cancers and its implication on stratification of patients for immune checkpoint inhibitor (ICI) therapy.

MATERIALS AND METHODS

This retrospective study used whole-exome sequencing (WES) to profile 1,233 Indian patients with cancer across 30 different cancer types and to estimate their TMB scores. A WES-based pipeline was adopted, along with an indigenously developed strategy for arriving at true somatic mutations. A robust unsupervised machine learning approach was used to understand the distribution of TMB scores across different populations and within the population.

RESULTS

The results of the study showed a biphasic distribution of TMB scores in most cancers, with different threshold scores across cancer types. Patients with cancer in India had higher TMB scores compared with the Caucasian patients. We also observed that the TMB score value at 90th percentile (predicting high efficacy to ICI) was high in four different cancer types (sarcoma, ovary, head and neck, and breast) in the Indian cohort as compared with The Cancer Genome Atlas or public cohort. However, in lung and colorectal cancers, the TMB score distribution was similar between the two population cohorts.

CONCLUSION

The findings of this study indicate that it is crucial to benchmark both cancer-specific and population-specific TMB distributions to establish a TMB threshold for each cancer in various populations. Additional prospective studies on much larger population across different cancers are warranted to validate this observation to become the standard of care.

An integrated analysis of microRNAs regulating DNA damage response in triple-negative breast cancer

BACKGROUND

Triple-negative breast cancer (TNBC) remains a clinical challenge due to its aggressive phenotype and limited treatment options for the patients. Many TNBC patients show an inherent defect in the DNA repair capacity primarily by acquiring germline mutations in BRCA1 and BRCA2 genes leading to Homologous Recombination Deficiency (HRD). Epigenetic modifications such as BRCA1 promoter methylation and miRNA expression targeting DNA repair pathway genes have contributed to the HRD phenotype in TNBC. Hence, we aimed to identify microRNAs that are associated with HRD status in the TCGA-BRCA project.

MATERIALS AND METHODS

We implemented a miRNA prediction strategy for identifying miRNAs targeting HR pathway genes using an in silico predicted and experimentally validated list from published literature for their association with genomic instability and factors affecting HRD. In silico analysis was performed to study miRNA expression patterns regulated by DNA methylation and TMB status in the TNBC patients from TCGA-BRCA project. Finally, we analysed selected miRNA expression with immune cell infiltration pattern in the TNBC patient cohort.

RESULTS

Our study identified miRNAs associated with HRD, tumour mutation burden (TMB), and immune cell infiltration. Identified miRNA signatures were associated with the miR-17 ~ 92 cluster, miR-106b ~ 25 cluster, and miR-200b ~ 429 cluster. Pathway analysis of selected miRNAs suggested their association with altered immune cell infiltration in TNBC.

CONCLUSION

Our study identified 6 'HRD associated miRNAs' such as miR-106b, miR-93, miR-17, miR-20a, miR-200b, and miR-429 as novel miRNA-based signatures associated with HR deficiency in TNBC.

The prognostic value of TMB in early-stage non-small cell lung cancer: a systematic review and meta-analysis

Background

Tumor mutation burden (TMB) has been validated as a predictive biomarker for immunotherapy response and survival in numerous cancer types. Limited data is available on the inherent prognostic role of TMB in early-stage tumors.

Objective

To evaluate the prognostic role of TMB in early-stage, resected non-small cell lung cancer (NSCLC).

Design

Systematic review and meta-analysis of pertinent prospective and retrospective studies.

Data sources and methods

Publication search was performed in PubMed, Embase, Cochrane Library, and Web of Science databases. Based on the level of heterogeneity, a random- or fixed-effects model was used to calculate pooled effects of hazard ratio (HR) for overall survival (OS) and disease-free survival (DFS). The source of heterogeneity was investigated using sensitivity analysis, subgroup analysis, and publication bias assessment.

Results

Ten studies comprising 2520 patients were included in this analysis. There was no statistically significant difference in OS (HR, 1.18, 95% CI, 0.70, 1.33; p 0.53, I2 = 80%; phet < 0.0001) and DFS (HR, 1.18, 95% CI, 0.91, 1.52; p = 0.53, I2 = 75%; phet = 0.0001) between the high-TMB and low-TMB group. Subgroup analyses indicated that East Asian ethnicity, and TMB detected using whole exome sequencing, and studies with <100 patients had poor DFS in the high-TMB group.

Conclusion

The inherent prognostic role of TMB is limited in early-stage NSCLC. Ethnic differences in mutation burden must be considered while designing future trials on neoadjuvant immunotherapy. Further research in the harmonization and standardization of panel-based TMB is essential for its widespread clinical utility.Registration: CRD42023392846.

Unraveling patient heterogeneity in complex diseases through individualized co-expression networks: a perspective

This perspective highlights the potential of individualized networks as a novel strategy for studying complex diseases through patient stratification, enabling advancements in precision medicine. We emphasize the impact of interpatient heterogeneity resulting from genetic and environmental factors and discuss how individualized networks improve our ability to develop treatments and enhance diagnostics. Integrating system biology, combining multimodal information such as genomic and clinical data has reached a tipping point, allowing the inference of biological networks at a single-individual resolution. This approach generates a specific biological network per sample, representing the individual from which the sample originated. The availability of individualized networks enables applications in personalized medicine, such as identifying malfunctions and selecting tailored treatments. In essence, reliable, individualized networks can expedite research progress in understanding drug response variability by modeling heterogeneity among individuals and enabling the personalized selection of pharmacological targets for treatment. Therefore, developing diverse and cost-effective approaches for generating these networks is crucial for widespread application in clinical services.

The Future of Precision Oncology

Our understanding of the molecular mechanisms underlying cancer development and evolution have evolved rapidly over recent years, and the variation from one patient to another is now widely recognized. Consequently, one-size-fits-all approaches to the treatment of cancer have been superseded by precision medicines that target specific disease characteristics, promising maximum clinical efficacy, minimal safety concerns, and reduced economic burden. While precision oncology has been very successful in the treatment of some tumors with specific characteristics, a large number of patients do not yet have access to precision medicines for their disease. The success of next-generation precision oncology depends on the discovery of new actionable disease characteristics, rapid, accurate, and comprehensive diagnosis of complex phenotypes within each patient, novel clinical trial designs with improved response rates, and worldwide access to novel targeted anticancer therapies for all patients. This review outlines some of the current technological trends, and highlights some of the complex multidisciplinary efforts that are underway to ensure that many more patients with cancer will be able to benefit from precision oncology in the near future.

Comparing Genomic Landscapes of Oral and Cutaneous Squamous Cell Carcinoma of the Head and Neck: Quest for Novel Diagnostic Markers

Squamous cell carcinoma is the most common head and neck malignancy arising from the oral mucosa and the skin. The histologic and immunohistochemical features of oral squamous cell carcinoma (OSCC) and head and neck cutaneous squamous cell carcinoma (HNcSCC) are similar, making it difficult to identify the primary site in cases of metastases. With the advent of immunotherapy, reliable distinction of OSCC and HNcSCC at metastatic sites has important treatment and prognostic implications. Here, we investigate and compare the genomic landscape of OSCC and HNcSCC to identify diagnostically useful biomarkers. Whole-genome sequencing data from 57 OSCC and 41 HNcSCC patients were obtained for tumor and matched normal samples. Tumor mutation burden (TMB), Catalogue of Somatic Mutations in Cancer (COSMIC) mutational signatures, frequent chromosomal alterations, somatic single nucleotide, and copy number variations were analyzed. The median TMB of 3.75 in primary OSCC was significantly lower (P < .001) than that of 147.51 mutations/Mb in primary HNcSCC. The COSMIC mutation signatures were significantly different (P < .001) between OSCC and HNcSCC. OSCC showed COSMIC single-base substitution (SBS) mutation signature 1 and AID/APOBEC activity-associated signature 2 and/or 13. All except 1 HNcSCC from hair-bearing scalp showed UV damage-associated COSMIC SBS mutation signature 7. Both OSCC and HNcSCC demonstrated a predominance of tumor suppressor gene mutations, predominantly TP53. The most frequently mutated oncogenes were PIK3CA and MUC4 in OSCC and HNcSCC, respectively. The metastases of OSCC and HNcSCC demonstrated TMB and COSMIC SBS mutation signatures similar to their primary counterparts. The combination of high TMB and UV signature in a metastatic keratinizing squamous cell carcinoma suggests HNcSCC as the primary site and may also facilitate decisions regarding immunotherapy. HNcSCC and OSCC show distinct genomic profiles despite histologic and immunohistochemical similarities. Their genomic characteristics may underlie differences in behavior and guide treatment decisions in recurrent and metastatic settings.

Next generation immuno-oncology biomarkers in gastrointestinal cancer: what does the future hold?

INTRODUCTION

Gastrointestinal (GI) cancers pose a significant health burden worldwide, necessitating advancements in diagnostic and treatment approaches. One promising avenue is the utilization of next-generation biomarkers, which hold the potential to revolutionize GI cancer management.

AREAS COVERED

This review explores the latest breakthroughs and expert opinions surrounding the application of next-generation immunotherapy biomarkers. It encompasses various aspects of the currently utilized biomarkers of immunotherapy in the context of GI cancers focusing on microsatellite stable cancers. It explores the promising research on the next generation of biomarkers addressing the challenges associated with integrating them into clinical practice and the need for standardized protocols and regulatory guidelines.

EXPERT OPINION

Immune profiling, multiplex immunohistochemistry, analysis of immune cell subsets, and novel genomic and epigenomic markers integrated with machine-learning approaches offer new avenues for identifying robust biomarkers. Liquid biopsy-based approaches, such as circulating tumor DNA (ctDNA) and exosome-based analyses, hold promise for real-time monitoring and early detection of treatment response.

Construction of the novel immune risk scoring system related to CD8+ T cells in uterine corpus endometrial carcinoma

BACKGROUND

Uterine corpus endometrial carcinoma (UCEC) is a gynecological malignant tumor with high incidence and poor prognosis. Although immunotherapy has brought significant survival benefits to advanced UCEC patients, traditional evaluation indicators cannot accurately identify all potential beneficiaries of immunotherapy. Consequently, it is necessary to construct a new scoring system to predict patient prognosis and responsiveness of immunotherapy.

METHODS

CIBERSORT combined with weighted gene co-expression network analysis (WGCNA), non-negative matrix factorization (NMF), and random forest algorithms to screen the module associated with CD8⁺ T cells, and key genes related to prognosis were selected out by univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses to develop the novel immune risk score (NIRS). Kaplan-Meier (K-M) analysis was used to compare the difference of survival between high- and low- NIRS groups. We  also explored the correlations between NIRS, immune infiltration and immunotherapy, and three external validation sets were used to verify the predictive performance of NIRS. Furthermore, clinical subgroup analysis, mutation analysis, differential expression of immune checkpoints, and drug sensitivity analysis were performed to generate individualized treatments for patients with different risk scores. Finally, gene set variation analysis (GSVA) was conducted to explore the biological functions of NIRS, and qRT-PCR was applied to verify the differential expressions of three trait genes at cellular and tissue levels.

RESULTS

Among the modules clustered by WGCNA, the magenta module was most positively associated with CD8⁺ T cells. Three genes (CTSW, CD3D and CD48) were selected to construct NIRS after multiple screening procedures. NIRS was confirmed as an independent prognostic factor of UCEC, and patients with high NIRS had significantly worse prognosis compared to those with low NIRS. The high NIRS group showed lower levels of infiltrated immune cells, gene mutations, and expression of multiple immune checkpoints, indicating reduced sensitivity to immunotherapy. Three module genes were identified as protective factors positively correlated with the level of CD8⁺ T cells.

CONCLUSIONS

In this study, we constructed NIRS as a novel predictive signature of UCEC. NIRS not only differentiates patients with distinct prognoses and immune responsiveness, but also guides their therapeutic regimens.

m6A reader YTHDF3 is associated with clinical prognosis, related RNA signatures and immunosuppression in gastric cancer

BACKGROUND

YTHDF3 as a N6-methyladenosine (m6A) reader participates in the development and progression of multiple cancer types, however, the prognosis, molecular biology and immune infiltration of YTHDF3 in gastric cancer (GC) have not been investigated.

METHODS

The YTHDF3 expression profile and clinicopathological parameters of stomach adenocarcinoma (STAD) were downloaded from TCGA. The online websites and databases such as GEPIA2, cBioPortal, UALCAN, ImmuCellAl, xCell, TISIDB, GSCA were utilized for analysis of the association of YTHDF3 with STAD, including clinical prognosis, WGCNA and LASSO Cox regression analysis. Further functional assays such as RT-qPCR, Western blot, immunohistochemistry (IHC), immunofluorescence (IF), CCK-8, colony formation, EdU and Transwell assays were performed to determine the role of YTHDF3 in GC.

RESULTS

We found that YTHDF3 was upregulated in STAD tissue samples ascribed to its copy number amplification and associated with poor prognosis in patients with STAD. GO and KEGG analyses showed that YTHDF3-related differential genes were predominantly enriched in the proliferation, metabolism and immune signaling pathways. Knockdown of YTHDF3 repressed the growth and invasion of GC cells by inhibition of PI3K/AKT signaling. We then identified YTHDF3-related lncRNAs, miRNAs and mRNAs, and constructed their prognostic signatures in patients with STAD. Moreover, YTHDF3 associated with tumor immune infiltration such as CD8+ T cells, macrophages, Tregs, MHC molecules and chemokines, upregulated PD-L1 and CXCL1 and exerted a response to the immunotherapy in GC.

CONCLUSIONS

YTHDF3 upregulation indicates poor prognosis and promotes GC cell growth and invasion by activating PI3K/AKT pathway and regulating immune microenvironment. The established YTHDF3-related signatures highlight the association of YTHDF3 with the clinical prognosis and immune cell infiltration in GC.

Immune-Checkpoint-Inhibitor Therapy-Principles and Relevance of Biomarkers for Pathologists and Oncologists

Immune-checkpoint-inhibitor (ICI) therapy has been one of the major advances in the treatment of a variety of advanced or metastatic tumors in recent years. Therefore, ICI-therapy is already approved in first-line therapy for multiple tumors, either as monotherapy or as combination therapy. However, there are relevant differences in approval among different tumor entities, especially with respect to PD-L1 testing. Different response to ICI-therapy has been observed in the pivotal trials, so PD-L1 diagnostic testing is used for patient selection. In addition to PD-L1 testing of tumor tissue, liquid biopsy provides a noninvasive way to monitor disease in cancer patients and identify those who would benefit most from ICI-therapy. This overview focuses on the use of ICI-therapy and how it relates to common and potential future biomarkers for patient-directed treatment planning.

Nivolumab plus ipilimumab combination therapy in cancer: Current evidence to date

Immune checkpoint inhibitors (ICIs) have revolutionized cancer immunotherapy, yielding significant antitumor responses across multiple cancer types. Combination ICI therapy with anti-CTLA-4 and anti-PD-1 antibodies outperforms either antibody alone in terms of clinical efficacy. As a consequence, the U.S. Food and Drug Administration (FDA) approved ipilimumab (anti-CTLA-4) plus nivolumab (anti-PD-1) as the first-ever approved therapies for combined ICI in patients with metastatic melanoma. Despite the success of ICIs, treatment with checkpoint inhibitor combinations poses significant clinical challenges, such as increased rates of immune-related adverse events (irAEs) and drug resistance. Thus, identifying optimal prognostic biomarkers could help to monitor the safety and efficacy of ICIs and identify patients who may benefit the most from these treatments. In this review, we will first go over the fundamentals of the CTLA-4 and PD-1 pathways, as well as the mechanisms of ICI resistance. The results of clinical findings that evaluated the combination of ipilimumab and nivolumab are then summarized to support future research in the field of combination therapy. Finally, the irAEs associated with combined ICI therapy, as well as the underlying biomarkers involved in their management, are discussed.

[New update to the guidelines on testing predictive biomarkers in non-small-cell lung cancer: a National Consensus of the Spanish Society of Pathology and the Spanish Society of Medical Oncology]

Non-small cell lung cancer (NSCLC) presents the greatest number of identified therapeutic targets, some of which have therapeutic utility. Currently, detecting EGFR, BRAF, KRAS and MET mutations, ALK, ROS1, NTRK and RET translocations, and PD-L1 expression in these patients is considered essential. The use of next-generation sequencing (NGS) facilitates precise molecular diagnosis and allows the detection of other emerging mutations, such as the HER2 mutation and predictive biomarkers for immunotherapy responses. In this consensus, a group of experts in the diagnosis and treatment of NSCLC selected by the Spanish Society of Pathology (SEAP) and the Spanish Society of Medical Oncology (SEOM) have evaluated currently available information and propose a series of recommendations to optimize the detection and use of biomarkers in daily clinical practice.

Liquid biopsy on the horizon in immunotherapy of non-small cell lung cancer: current status, challenges, and perspectives

Non-small cell lung cancer (NSCLC) is one of the most threatening malignancies to human health and life. In most cases, patients with NSCLC are already at an advanced stage when they are diagnosed. In recent years, lung cancer has made great progress in precision therapy, but the efficacy of immunotherapy is unstable, and its response rate varies from patient to patient. Several biomarkers have been proposed to predict the outcomes of immunotherapy, such as programmed cell death-ligand 1 (PD-L1) expression and tumor mutational burden (TMB). Nevertheless, the detection assays are invasive and demanding on tumor tissue. To effectively predict the outcomes of immunotherapy, novel biomarkers are needed to improve the performance of conventional biomarkers. Liquid biopsy is to capture and detect circulating tumor cells (CTCs), circulating tumor DNA (ctDNA) and exosomes in body fluids, such as blood, saliva, urine, pleural fluid and cerebrospinal fluid as samples from patients, so as to make analysis and diagnosis of cancer and other diseases. The application of liquid biopsy provides a new possible solution, as it has several advantages such as non-invasive, real-time dynamic monitoring, and overcoming tumor heterogeneity. Liquid biopsy has shown predictive value in immunotherapy, significantly improving the precision treatment of lung cancer patients. Herein, we review the application of liquid biopsy in predicting the outcomes of immunotherapy in NSCLC patients, and discuss the challenges and future directions in this field.

Identification of immune related molecular subtypes and prognosis model for predicting prognosis, drug resistance in cervical squamous cell carcinoma

Background: One of the features of tumor immunity is the immunosuppressive tumor microenvironment (TME). In this study, TME gene signatures were used to define the characteristics of Cervical squamous cell carcinoma (CESC) immune subtypes and construct a new prognostic model.

Methods: Single sample gene set enrichment analysis (ssGSEA) was used to quantify pathway activity. RNA-seq of 291 CESC were obtained from the Cancer Genome Atlas (TCGA) database as a training set. Microarray-based data of 400 cases of CESC were obtained from the Gene Expression Compilation (GEO) database as an independent validation set. 29 TME related gene signatures were consulted from previous study. Consensus Cluster Plus was employed to identify molecular subtype. Univariate cox regression analysis and random survival forest (RSF) were used to establish the immune-related gene risk model based on the TCGA data set of CESC, and the accuracy of prognosis prediction was verified by GEO data set. ESTIMATE algorithm was used to perform immune and matrix scores on the data set.

Results: three molecular subtypes (C1, C2, C3) were screened in TCGA-CESC on account of 29 TME gene signatures. Among, C3 with better survival outcome had higher immune related gene signatures, while C1 with worse prognosis time had enhanced matrix related features. Increased immune infiltration, inhibition of tumor related pathways, widespread genomic mutations and prone immunotherapy were observed in C3. Furthermore, a five immune genes signature was constructed and predicted overall survival for CESC, which successfully validated in GSE44001 dataset. A positive phenomenon was observed between five hub genes expressions and methylation. Similarly, high group enriched in matrix related features, while immune related gene signatures were enriched in low group. Immune cell, immune checkpoints genes expression levels were negatively, while most TME gene signatures were positively correlated with Risk Score. In addition, high group was more sensitive to drug resistance.

Conclusion: This work identified three distinct immune subtypes and a five genes signature for predicting prognosis in CESC patients, which provided a promising treatment strategy for CESC.