A genomic mutation signature predicts the clinical outcomes of immunotherapy and characterizes immunophenotypes in gastrointestinal cancer

AI-powered genomic mutation signature for predicting immune checkpoint inhibitor therapy outcomes in gastroesophageal cancer: a multi-cohort analysis

BACKGROUND

Immune checkpoint inhibitors (ICIs) have significantly transformed the treatment of gastroesophageal cancer (GEC). However, the lack of reliable prognostic biomarkers hinders the ability to predict patient response to ICI therapy.

METHODS

In this study, we engineered and validated a genomic mutation signature (GMS) utilizing an innovative artificial intelligence (AI) algorithm to forecast ICI therapy outcomes in GEC patients. We further explored immune profiles across subtypes through comprehensive multiomics analysis. Our investigation of drug sensitivity data from the Genomics of Drug Sensitivity in Cancer (GDSC) database led to the identification of trametinib as a potential therapeutic agent. We subsequently evaluated trametinib's efficacy in AGS and MKN45 cell lines using Cell Counting Kit-8 (CCK8) assays and clonogenic experiments.

RESULTS

We developed a GMS by integrating 297 algorithms, enabling autonomous prognosis prediction for GEC patients. The GMS demonstrated consistent performance across three public cohorts, exhibiting high sensitivity and specificity for overall survival (OS) at 6, 12, and 18 months, as shown by Receiver Operator Characteristic Curve (ROC) analysis. Notably, the GMS surpassed traditional clinical and molecular features, including tumor mutational burden (TMB), programmed death-ligand 1 (PD-L1) expression, and microsatellite instability (MSI), in predictive accuracy. Low-risk samples exhibited elevated levels of cytolytic immune cells and heightened immunogenic potential compared to high-risk samples. Our investigation identified trametinib as a potential therapeutic agent. An inverse correlation was observed between GMS and trametinib IC50. Moreover, the high-risk-derived AGS cell line showed increased sensitivity to trametinib compared to the low-risk-derived MKN45 cell line.

CONCLUSION

The GMS utilized in this study successfully demonstrated the ability to reliably predict the survival advantage for patients with GECs undergoing ICI therapy.

Prognostic Signature in Osteosarcoma Based on Amino Acid Metabolism-Associated Genes

Background: Osteosarcoma (OS) is undeniably a formidable bone malignancy characterized by a scarcity of effective treatment options. Reprogramming of amino acid (AA) metabolism has been associated with OS development. The present study was designed to identify metabolism-associated genes (MAGs) that are differentially expressed in OS and to construct a MAG-based prognostic risk signature for this disease. Methods: Expression profiles and clinicopathological data were downloaded from Gene Expression Omnibus (GEO) and UCSC Xena databases. A set of AA MAGs was obtained from the MSigDB database. Differentially expressed genes (DEGs) in GEO dataset were identified using "limma." Prognostic MAGs from UCSC Xena database were determined through univariate Cox regression and used in the prognostic signature development. This signature was validated using another dataset from GEO database. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, single sample gene set enrichment analysis, and GDSC2 analyses were performed to explore the biological functions of the MAGs. A MAG-based nomogram was established to predict 1-, 3-, and 5-year survival. Real-time quantitative polymerase chain reaction, Western blot, and immunohistochemical staining confirmed the expression of MAGs in primary OS and paired adjacent normal tissues. Results: A total of 790 DEGs and 62 prognostic MAGs were identified. A MAG-based signature was constructed based on four MAGs: PIPOX, PSMC2, SMOX, and PSAT1. The prognostic value of this signature was successfully validated, with areas under the receiver operating characteristic curves for 1-, 3-, and 5-year survival of 0.714, 0.719, and 0.715, respectively. This MAG-based signature was correlated with the infiltration of CD56dim natural killer cells and resistance to several antiangiogenic agents. The nomogram was accurate in predictions, with a C-index of 0.77. The expression of MAGs verified by experiment was consistent with the trends observed in GEO database. Conclusion: Four AA MAGs were prognostic of survival in OS patients. This MAG-based signature has the potential to offer valuable insights into the development of treatments for OS.

Recent developments in immunotherapy for gastrointestinal tract cancers

The past few decades have witnessed the rise of immunotherapy for Gastrointestinal (GI) tract cancers. The role of immune checkpoint inhibitors (ICIs), particularly programmed death protein 1 (PD-1) and PD ligand-1 antibodies, has become increasingly pivotal in the treatment of advanced and perioperative GI tract cancers. Currently, anti-PD-1 plus chemotherapy is considered as first-line regimen for unselected advanced gastric/gastroesophageal junction adenocarcinoma (G/GEJC), mismatch repair deficient (dMMR)/microsatellite instability-high (MSI-H) colorectal cancer (CRC), and advanced esophageal cancer (EC). In addition, the encouraging performance of claudin18.2-redirected chimeric antigen receptor T-cell (CAR-T) therapy in later-line GI tract cancers brings new hope for cell therapy in solid tumour treatment. Nevertheless, immunotherapy for GI tumour remains yet precise, and researchers are dedicated to further maximising and optimising the efficacy. This review summarises the important research, latest progress, and future directions of immunotherapy for GI tract cancers including EC, G/GEJC, and CRC.

A novel artificial intelligence network to assess the prognosis of gastrointestinal cancer to immunotherapy based on genetic mutation features

Background

Immune checkpoint inhibitors (ICIs) have revolutionized gastrointestinal cancer treatment, yet the absence of reliable biomarkers hampers precise patient response prediction.

Methods

We developed and validated a genomic mutation signature (GMS) employing a novel artificial intelligence network to forecast the prognosis of gastrointestinal cancer patients undergoing ICIs therapy. Subsequently, we explored the underlying immune landscapes across different subtypes using multiomics data. Finally, UMI-77 was pinpointed through the analysis of drug sensitization data from the Genomics of Drug Sensitivity in Cancer (GDSC) database. The sensitivity of UMI-77 to the AGS and MKN45 cell lines was evaluated using the cell counting kit-8 (CCK8) assay and the plate clone formation assay.

Results

Using the artificial intelligence network, we developed the GMS that independently predicts the prognosis of gastrointestinal cancer patients. The GMS demonstrated consistent performance across three public cohorts and exhibited high sensitivity and specificity for 6, 12, and 24-month overall survival (OS) in receiver operating characteristic (ROC) curve analysis. It outperformed conventional clinical and molecular features. Low-risk samples showed a higher presence of cytolytic immune cells and enhanced immunogenic potential compared to high-risk samples. Additionally, we identified the small molecule compound UMI-77. The half-maximal inhibitory concentration (IC50) of UMI-77 was inversely related to the GMS. Notably, the AGS cell line, classified as high-risk, displayed greater sensitivity to UMI-77, whereas the MKN45 cell line, classified as low-risk, showed less sensitivity.

Conclusion

The GMS developed here can reliably predict survival benefit for gastrointestinal cancer patients on ICIs therapy.

PTCH1 mutation as a potential predictive biomarker for immune checkpoint inhibitors in gastrointestinal cancer

Immune checkpoint inhibitors (ICIs) have become prominent therapies for gastrointestinal cancer (GC). However, it is urgent to screen patients who can benefit from ICIs. Protein patched homolog 1 (PTCH1) is a frequently altered gene in GC. We attempt to explore the association between PTCH1 mutation and immunotherapy efficacy. The Memorial Sloan Kettering Cancer Center (MSKCC) cohort (n = 236) with GC (esophageal, gastric and colorectal cancers) patients receiving ICIs was used for discovery and the Peking University Cancer Hospital (PUCH) GC cohort (n = 92) was used for validation. Overall survival (OS) and tumor mutational burden (TMB) of the PTCH1 mutant-type (PTCH1-MUT) and PTCH1 wild-type (PTCH1-WT) groups were compared. Furthermore, GC data were collected from The Cancer Genome Atlas to assess the potential mechanisms. In the MSKCC cohort, PTCH1-MUT group showed significantly better OS (P = 0.017) and higher TMB. Multivariate analysis showed that PTCH1 mutation was associated with better OS. In the PUCH cohort, PTCH1-MUT group showed significantly longer OS (P = 0.036) and progression-free survival, and higher durable clinical benefit and TMB. Immune cell infiltration analysis revealed that PTCH1-MUT group had significantly higher distributions of CD8 T cells, CD4 T cells, NK cells, mast cells and M1 cells. The PTCH1-MUT group showed significantly higher expression of most immune-related genes. Gene set enrichment analysis showed that the PTCH1-MUT group had enriched INF-γ response, INF-α response, glycolysis and reactive oxygen species pathway gene sets. PTCH1 mutation may represent a potential biomarker for predicting ICIs response in GC. Nevertheless, prospective cohort studies should be performed to further validate our results.

A recurrence-predictive model based on eight genes and tumor mutational burden/microsatellite instability status in Stage II/III colorectal cancer

BACKGROUND

Although adjuvant chemotherapy (ACT) is widely used to treat patients with Stage II/III colorectal cancer (CRC), administering ACT to specific patients remains a challenge. The decision to ACT requires an accurate assessment of recurrence risk and absolute treatment benefit. However, the traditional TNM staging system does not accurately assess a patient's individual risk of recurrence.

METHODS

To identify recurrence risk-related genetic factors for Stage II/III CRC patients after radical surgery, we conducted an analysis of whole-exome sequencing of 47 patients with Stage II/III CRC who underwent radical surgery at five institutions. Patients were grouped into non-recurrence group (NR, n = 24, recurrence-free survival [RFS] > 5 years) and recurrence group (R, n = 23, RFS <2 years). The TCGA-COAD/READ cohort was employed as the validation dataset.

RESULTS

A recurrence-predictive model (G8plus score) based on eight gene (CUL9, PCDHA12, HECTD3, DCX, SMARCA2, FAM193A, AATK, and SORCS2) mutations and tumor mutation burden/microsatellite instability (TMB/MSI) status was constructed, with 97.87% accuracy in our data and 100% negative predictive value in the TCGA-COAD/READ cohort. For the TCGA-COAD/READ cohort, the G8plus-high group had better RFS (HR = 0.22, p = 0.024); the G8plus-high tumors had significantly more infiltrated immune cell types, higher tertiary lymphoid structure signature scores, and higher immunological signature scores. The G8plus score was also a predict biomarker for immunotherapeutic in advanced CRC in the PUCH cohort.

CONCLUSIONS

In conclusion, the G8plus score is a powerful biomarker for predicting the risk of recurrence in patients with stage II/III CRC. It can be used to stratify patients who benefit from ACT and immunotherapy.

PD-L1 expression-related PI3K pathway correlates with immunotherapy efficacy in gastric cancer

Background

The programed death ligand-1 combined positive score (PD-L1 CPS), the only FDA-approved biomarker for immune checkpoint inhibitor therapy in gastric cancer (GC) patients, is an important but imperfect predictive biomarker. The molecular characteristics of tumors that influence the PD-L1 CPS are largely unknown and would be helpful for screening patients who would benefit from immunotherapy.

Methods

PD-L1 immunohistochemistry (IHC) and targeted next-generation sequencing techniques were used to compare genomic alterations in 492 GC patients in two groups (PD-L1 CPS ⩾ 1, positive; CPS < 1, negative). Screened PD-L1 expression-related factors were analyzed for immunotherapy efficacy in three distinct GC cohorts from public databases.

Results

Positive PD-L1 expression occurred in 40% of GC patients and was associated with a higher proportion of phosphatidylinositol 3-kinase (PI3K), SWItch/Sucrose NonFermentable (SWI/SNF), lysine demethylase (KDM), and DNA (cytosine-5)-methyltransferase (DNMT) (all p < 0.01), pathway alterations. Compared to wild-type GC patients, those with PI3K pathway alterations had a higher response rate (p = 0.002) and durable clinical benefit rate with immunotherapy (p = 0.023, p = 0.038) as well as longer progression-free survival (p = 0.084, p = 0.0076) and overall survival (p = 0.2, p = 0.037) with immunotherapy.

Conclusion

This study revealed PD-L1 expression-related factors in the tumor genome in a GC cohort. Alterations in the PI3K pathway associated with PD-L1 positivity were shown to be associated with better immunotherapy efficacy in three distinct GC cohorts from public databases. Our results provide a potential avenue for patient selection and rational immune combination development for GC patients.

Pan-cancer analysis of NFE2L2 mutations identifies a subset of lung cancers with distinct genomic and improved immunotherapy outcomes

BACKGROUND

Mutations in the KEAP1-NFE2L2 signaling pathway were linked to increased tumorigenesis and aggressiveness. Interestingly, not all hotspot mutations on NFE2L2 were damaging; some even were activating. However, there was conflicting evidence about the association between NFE2L2 mutation and Nrf2-activating mutation and responsiveness to immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC) and other multiple cancers.

METHODS

The study with the largest sample size (n = 49,533) explored the landscape of NFE2L2 mutations and their impact response/resistance to ICIs using public cohorts. In addition, the in-house WXPH cohort was used to validate the efficacy of immunotherapy in the NFE2L2 mutated patients with NSCLC.

RESULTS

In two pan-cancer cohorts, Nrf2-activating mutation was associated with higher TMB value compared to wild-type. We identified a significant association between Nrf2-activating mutation and shorter overall survival in pan-cancer patients and NSCLC patients but not in those undergoing ICIs treatment. Similar findings were obtained in cancer patients carrying the NFE2L2 mutation. Furthermore, in NSCLC and other cancer cohorts, patients with NFE2L2 mutation demonstrated more objective responses to ICIs than patients with wild type. Our in-house WXPH cohort further confirmed the efficacy of immunotherapy in the NFE2L2 mutated patients with NSCLC. Lastly, decreased inflammatory signaling pathways and immune-depleted immunological microenvironments were enriched in Nrf2-activating mutation patients with NSCLC.

CONCLUSIONS

Our study found that patients with Nrf2-activating mutation had improved immunotherapy outcomes than patients with wild type in NSCLC and other tumor cohorts, implying that Nrf2-activating mutation defined a distinct subset of pan-cancers and might have implications as a biomarker for guiding ICI treatment, especially NSCLC.

Genotype-specific precision tumor therapy using mitochondrial DNA mutation-induced drug release system

Precise killing of tumor cells without affecting surrounding normal cells is a challenge. Mitochondrial DNA (mtDNA) mutations, a common genetic variant in cancer, can directly affect metabolic homeostasis, serving as an ideal regulatory switch for precise tumor therapy. Here, we designed a mutation-induced drug release system (MIDRS), using the single-nucleotide variation (SNV) recognition ability and trans-cleavage activity of Cas12a to convert tumor-specific mtDNA mutations into a regulatory switch for intracellular drug release, realizing precise tumor cell killing. Using Ce6 as a model drug, MIDRS enabled organelle-level photodynamic therapy, triggering innate and adaptive immunity simultaneously. In vivo evaluation showed that MIDRSMT could identify tumor tissue carrying SNVs in mtDNA in unilateral, bilateral, and heterogeneous tumor models, producing an excellent antitumor effect (~82.6%) without affecting normal cells and thus resulting in a stronger systemic antitumor immune response. Additionally, MIDRS was suitable for genotype-specific precision drug release of chemotherapeutic drugs. This strategy holds promise for mutation-specific personalized tumor treatment approaches.

Mutational Signatures in Gastric Cancer and Their Clinical Implications

Gastric cancer is characterised by high inter- and intratumour heterogeneity. The majority of patients are older than 65 years and the global burden of this disease is increasing due to the aging of the population. The disease is usually diagnosed at advanced stages, which is a consequence of nonspecific symptoms. Few improvements have been made at the level of noninvasive molecular diagnosis of sporadic gastric cancer, and therefore the mortality rate remains high. A new field of mutational signatures has emerged in the past decade with advances in the genome sequencing technology. These distinct mutational patterns in the genome, caused by exogenous and endogenous mutational processes, can be associated with tumour aetiology and disease progression, and could provide novel perception on the treatment possibilities. This review assesses the mutational signatures found in gastric cancer and summarises their potential for use in clinical setting as diagnostic or prognostic biomarkers. Associated treatment options and biomarkers already implemented in clinical use are discussed, together with those that are still being explored or are in clinical studies.

SWI/SNF Complex Genomic Alterations as a Predictive Biomarker for Response to Immune Checkpoint Inhibitors in Multiple Cancers

Whether there is an association between SWI/SNF genomic alterations in tumors and response to immune checkpoint inhibitors (ICI) remains unclear because prior studies have focused on either an individual gene or a predefined set of genes. Herein, using mutational and clinical data from 832 ICI-treated patients who underwent whole-exome sequencing, including sequencing of all 31 genes of the SWI/SNF complex, we found that SWI/SNF complex alterations were associated with significantly improved overall survival (OS) in melanoma, clear-cell renal cell carcinoma, and gastrointestinal cancer, as well as improved progression-free survival (PFS) in non-small cell lung cancer. Including tumor mutational burden as a variable, the multivariate Cox regression analysis showed SWI/SNF genomic alterations had prognostic value in melanoma [HR, 0.63 (95% confidence interval, CI, 0.47-0.85), P = 0.003], clear-cell renal cell carcinoma [HR, 0.62 (95% CI, 0.46-0.85), P = 0.003], and gastrointestinal cancer [HR, 0.42 (95% CI, 0.18-1.01), P = 0.053]. Furthermore, we used the random forest method for variable screening, identifying 14 genes as a SWI/SNF signature for potential clinical application. Significant correlations were observed between SWI/SNF signature alterations and improved OS and PFS in all cohorts. This suggests that SWI/SNF gene alterations are associated with better clinical outcomes in ICI-treated patients and may serve as a predictive marker for ICI therapy in multiple cancers.

Mutational analysis of microsatellite-stable gastrointestinal cancer with high tumour mutational burden: a retrospective cohort study

BACKGROUND

Genomic signatures contributing to high tumour mutational burden (TMB-H) independent from mismatch-repair deficiency (dMMR) or microsatellite instability-high (MSI-H) status are not well studied. We aimed to characterise molecular features of microsatellite stable (MSS) TMB-H gastrointestinal tumours.

METHODS

Molecular alterations of 48 606 gastrointestinal tumours from Caris Life Sciences (CARIS) identified with next-generation sequencing were compared among MSS-TMB-H, dMMR/MSI-H, and MSS-TMB-low (L) tumours, using χ2 or Fisher's exact tests. Antitumour immune response within the tumour environment was predicted by analysing the infiltration of immune cells and immune signatures using The Cancer Genome Atlas database. The Kaplan-Meier method and the log-rank test were used to evaluate the impact of gene alterations on the efficacy of immune checkpoint inhibitors in MSS gastrointestinal cancers from the CARIS database, a Memorial Sloan Kettering Cancer Center cohort, and a Peking University Cancer Hospital cohort.

FINDINGS

MSS-TMB-H was observed in 1600 (3·29%) of 48 606 tumours, dMMR/MSI-H in 2272 (4·67%), and MSS-TMB-L in 44 734 (92·03%). Gene mutations in SMAD2, MTOR, NFE2L2, RB1, KEAP1, TERT, and RASA1 might impair antitumour immune response despite TMB-H, while mutations in 16 other genes (CDC73, CTNNA1, ERBB4, EZH2, JAK2, MAP2K1, MAP2K4, PIK3R1, POLE, PPP2R1A, PPP2R2A, PTPN11, RAF1, RUNX1, STAG2, and XPO1) were related to TMB-H with enhanced antitumour immune response independent of dMMR/MSI-H, constructing a predictive model (modified TMB [mTMB]) for immune checkpoint inhibitor efficacy. Patients with any mutation in the mTMB gene signature, in comparison with patients with mTMB wildtype tumours, showed a superior survival benefit from immune checkpoint inhibitors in MSS gastrointestinal cancers in the CARIS cohort (n=95, median overall survival 18·77 months [95% CI 17·30-20·23] vs 7·03 months [5·73-8·34]; hazard ratio 0·55 [95% CI 0·31-0·99], p=0·044). In addition, copy number amplification in chromosome 11q13 (eg, CCND1, FGF genes) was more prevalent in MSS-TMB-H tumours than in the dMMR/MSI-H or MSS-TMB-L subgroups.

INTERPRETATION

Not all mutations related to TMB-H can enhance antitumour immune response. More composite biomarkers should be investigated (eg, mTMB signature) to tailor treatment with immune checkpoint inhibitors. Our data also provide novel insights for the combination of immune checkpoint inhibitors and drugs targeting cyclin D1 or FGFs.

FUNDING

US National Cancer Institute, Gloria Borges WunderGlo Foundation, Dhont Family Foundation, Gene Gregg Pancreas Research Fund, San Pedro Peninsula Cancer Guild, Daniel Butler Research Fund, Victoria and Philip Wilson Research Fund, Fong Research Project, Ming Hsieh Research Fund, Shanghai Sailing Program, China National Postdoctoral Program for Innovative Talents, China Postdoctoral Science Foundation, National Natural Science Foundation of China.

A pathway-based mutation signature to predict the clinical outcomes and response to CTLA-4 inhibitors in melanoma

Immune checkpoint inhibitor (ICI) therapy has become a powerful clinical strategy for treating melanoma. The relationship between somatic mutations and the clinical benefits of immunotherapy has been widely recognized. However, the gene-based predictive biomarkers are less stable due to the heterogeneity of cancer at the individual gene level. Recent studies have suggested that the accumulation of gene mutations in biological pathways may activate antitumor immune responses. Herein, a novel pathway mutation signature (PMS) was constructed to predict the survival and efficacy of ICI therapy. In a dataset of melanoma patients treated with anti-CTLA-4, we mapped the mutated genes into the pathways and then identified seven significant mutation pathways associated with survival and immunotherapy response, which were used to construct the PMS model. According to the PMS model, the patients in the PMS-high group showed better overall survival (hazard ratio (HR) = 0.37; log-rank test, p < 0.0001) and progression-free survival (HR = 0.52; log-rank test, p = 0.014) than those in the PMS-low group. The PMS-high patients also showed a significantly higher objective response rate to anti-CTLA-4 therapy than the PMS-low patients (Fisher's exact test, p = 0.0055), and the predictive power of the PMS model was superior to that of TMB. Finally, the prognostic and predictive value of the PMS model was validated in two independent validation sets. Our study demonstrated that the PMS model can be considered a potential biomarker to predict the clinical outcomes and response to anti-CTLA-4 therapy in melanoma patients.

Identification and validation of a genomic mutation signature as a predictor for immunotherapy in NSCLC

Currently, the benefits of immune checkpoint inhibitor (ICI) therapy prediction via emerging biomarkers have been identified, and the association between genomic mutation signatures (GMS) and immunotherapy benefits has been widely recognized as well. However, the evidence about non-small cell lung cancer (NSCLC) remains limited. We analyzed 310 immunotherapy patients with NSCLC from the Memorial Sloan Kettering Cancer Center (MSKCC) cohort. Lasso Cox regression was used to construct a GMS, and the prognostic value of GMS could be able to verify in the Rizvi cohort (N=240) and Hellmann cohort (N=75). We further conducted immunotherapy-related characteristics analysis in The Cancer Genome Atlas (TCGA) cohort (N=1052). A total of seven genes (ZFHX3, NTRK3, EPHA7, MGA, STK11, EPHA5, TP53) were identified for GMS model construction. Compared with GMS-high patients, patients with GMS-low had longer overall survival (OS; P<0.001) in the MSKCC cohort and progression-free survival (PFS; P<0.001) in the validation cohort. Multivariate Cox analysis revealed that GMS was an independent predictive factor for NSCLC patients in both the MSKCC and validation cohort. Meanwhile, we found that GMS-low patients reflected enhanced antitumor immunity in TCGA cohort. The results indicated that GMS had not only potential predictive value for the benefit of immunotherapy but also may serve as a potential biomarker to guide clinical ICI treatment decisions for NSCLC.

Enhanced Permeability and Retention Effect as a Ubiquitous and Epoch-Making Phenomenon for the Selective Drug Targeting of Solid Tumors

In 1979, development of the first polymer drug SMANCS [styrene-co-maleic acid (SMA) copolymer conjugated to neocarzinostatin (NCS)] by Maeda and colleagues was a breakthrough in the cancer field. When SMANCS was administered to mice, drug accumulation in tumors was markedly increased compared with accumulation of the parental drug NCS. This momentous result led to discovery of the enhanced permeability and retention effect (EPR effect) in 1986. Later, the EPR effect became known worldwide, especially in nanomedicine, and is still believed to be a universal mechanism for tumor-selective accumulation of nanomedicines. Some research groups recently characterized the EPR effect as a controversial concept and stated that it has not been fully demonstrated in clinical settings, but this erroneous belief is due to non-standard drug design and use of inappropriate tumor models in investigations. Many research groups recently provided solid evidence of the EPR effect in human cancers (e.g., renal and breast), with significant diversity and heterogeneity in various patients. In this review, we focus on the dynamics of the EPR effect and restoring tumor blood flow by using EPR effect enhancers. We also discuss new applications of EPR-based nanomedicine in boron neutron capture therapy and photodynamic therapy for solid tumors.

Clinical Applications of Liquid Biopsy in Colorectal Cancer Screening: Current Challenges and Future Perspectives

Colorectal cancer (CRC) represents the third most prevalent cancer worldwide and a leading cause of mortality among the population of western countries. However, CRC is frequently a preventable malignancy due to various screening tests being available. While failing to obtain real-time data, current screening methods (either endoscopic or stool-based tests) also require disagreeable preparation protocols and tissue sampling through invasive procedures, rendering adherence to CRC screening programs suboptimal. In this context, the necessity for novel, less invasive biomarkers able to identify and assess cancer at an early stage is evident. Liquid biopsy comes as a promising minimally invasive diagnostic tool, able to provide comprehensive information on tumor heterogeneity and dynamics during carcinogenesis. This review focuses on the potential use of circulating tumor cells (CTCs), circulating nucleic acids (CNAs) and extracellular vesicles as emerging liquid biopsy markers with clinical application in the setting of CRC screening. The review also examines the opportunity to implement liquid biopsy analysis during everyday practice and provides highlights on clinical trials researching blood tests designed for early cancer diagnosis. Additionally, the review explores potential applications of liquid biopsies in the era of immunotherapy.

Pancancer analysis of a potential gene mutation model in the prediction of immunotherapy outcomes

Background: Immune checkpoint blockade (ICB) represents a promising treatment for cancer, but predictive biomarkers are needed. We aimed to develop a cost-effective signature to predict immunotherapy benefits across cancers.

Methods: We proposed a study framework to construct the signature. Specifically, we built a multivariate Cox proportional hazards regression model with LASSO using 80% of an ICB-treated cohort (n = 1661) from MSKCC. The desired signature named SIGP was the risk score of the model and was validated in the remaining 20% of patients and an external ICB-treated cohort (n = 249) from DFCI.

Results: SIGP was based on 18 candidate genes (NOTCH3, CREBBP, RNF43, PTPRD, FAM46C, SETD2, PTPRT, TERT, TET1, ROS1, NTRK3, PAK7, BRAF, LATS1, IL7R, VHL, TP53, and STK11), and we classified patients into SIGP high (SIGP-H), SIGP low (SIGP-L) and SIGP wild type (SIGP-WT) groups according to the SIGP score. A multicohort validation demonstrated that patients in SIGP-L had significantly longer overall survival (OS) in the context of ICB therapy than those in SIGP-WT and SIGP-H (44.00 months versus 13.00 months and 14.00 months, p &lt; 0.001 in the test set). The survival of patients grouped by SIGP in non-ICB-treated cohorts was different, and SIGP-WT performed better than the other groups. In addition, SIGP-L + TMB-L (approximately 15% of patients) had similar survivals to TMB-H, and patients with both SIGP-L and TMB-H had better survival. Further analysis on tumor-infiltrating lymphocytes demonstrated that the SIGP-L group had significantly increased abundances of CD8+ T cells.

Conclusion: Our proposed model of the SIGP signature based on 18-gene mutations has good predictive value for the clinical benefit of ICB in pancancer patients. Additional patients without TMB-H were identified by SIGP as potential candidates for ICB, and the combination of both signatures showed better performance than the single signature.

Functional Impact of Risk Gene Variants on the Autoimmune Responses in Type 1 Diabetes

Type 1 diabetes (T1D) is an autoimmune disease that develops in the interplay between genetic and environmental factors. A majority of individuals who develop T1D have a HLA make up, that accounts for 50% of the genetic risk of disease. Besides these HLA haplotypes and the insulin region that importantly contribute to the heritable component, genome-wide association studies have identified many polymorphisms in over 60 non-HLA gene regions that also contribute to T1D susceptibility.

Combining the risk genes in a score (T1D-GRS), significantly improved the prediction of disease progression in autoantibody positive individuals. Many of these minor-risk SNPs are associated with immune genes but how they influence the gene and protein expression and whether they cause functional changes on a cellular level remains a subject of investigation. A positive correlation between the genetic risk and the intensity of the peripheral autoimmune response was demonstrated both for HLA and non-HLA genetic risk variants. We also observed epigenetic and genetic modulation of several of these T1D susceptibility genes in dendritic cells (DCs) treated with vitamin D3 and dexamethasone to acquire tolerogenic properties as compared to immune activating DCs (mDC) illustrating the interaction between genes and environment that collectively determines risk for T1D. A notion that targeting such genes for therapeutic modulation could be compatible with correction of the impaired immune response, inspired us to review the current knowledge on the immune-related minor risk genes, their expression and function in immune cells, and how they may contribute to activation of autoreactive T cells, Treg function or β-cell apoptosis, thus contributing to development of the autoimmune disease.

A Neutrophil Extracellular Traps Signature Predicts the Clinical Outcomes and Immunotherapy Response in Head and Neck Squamous Cell Carcinoma

Background: Neutrophil extracellular traps (NETs) play an important role in the occurrence, metastasis and immune escape of cancers. This study aimed to investigate NET-related genes, their clinical prognostic value and their correlation with immunotherapy and anticancer drugs in patients with head and neck squamous cell carcinoma (HNSCC).

Methods: Differentially expressed NET-related genes in HNSCC were identified based on multiple public databases. To improve the clinical practicability and avoid overfitting, univariable, least absolute shrinkage and selection operator (LASSO) and multivariable Cox algorithms were used to construct a prognostic risk model. A nomogram was further used to explore the clinical value of the model. Internal and external validation were conducted to test the model. Furthermore, the immune microenvironment, immunophenoscore (IPS) and sensitivity to anticancer drugs in HNSCC patients with different prognostic risks were explored.

Results: Six NET-related genes were screened to construct the risk model. In the training cohort, Kaplan–Meier (K-M) analysis showed that the overall survival (OS) of low-risk HNSCC patients was significantly better than that of high-risk HNSCC patients (p < 0.001). The nomogram also showed a promising prognostic value with a better C-index (0.726 vs 0.640) and area under the curve (AUC) (0.743 vs 0.706 at 3 years, 0.743 vs 0.645 at 5 years) than those in previous studies. Calibration plots and decision curve analysis (DCA) also showed the satisfactory predictive capacity of the nomogram. Internal and external validation further strengthened the credibility of the clinical prognostic model. The level of tumor mutational burden (TMB) in the high-risk group was significantly higher than that in the low-risk group (p = 0.017), and the TMB was positively correlated with the risk score (R = 0.11; p = 0.019). Moreover, the difference in immune infiltration was significant in HNSCC patients with different risks (p < 0.05). Furthermore, the IPS analysis indicated that anti-PD-1 (p < 0.001), anti-CTLA4 (p < 0.001) or combining immunotherapies (p < 0.001) were more beneficial for low-risk HNSCC patients. The response to anticancer drugs was also closely correlated with the expression of NET-related genes (p < 0.001).

Conclusion: This study identified a novel prognostic model that might be beneficial to develop personalized treatment for HNSCC patients.

The combination of gene hyperamplification and PD-L1 expression as a biomarker for the clinical benefit of tislelizumab in gastric/gastroesophageal junction adenocarcinoma

BACKGROUND

In solid tumor Phase 1/2 trials (NCT02407990; NCT04068519), tislelizumab demonstrated clinical benefit, including in advanced gastroesophageal adenocarcinoma (GEA). However, the majority of patients with GEA did not respond, highlighting the need to understand mechanisms of resistance and identify predictive biomarkers for response.

METHODS

All tislelizumab-treated patients with GEA from the Phase 1/2 trials were included (N = 105). Programmed death-ligand 1 (PD-L1) expression (Tumor Area Positivity [TAP] ≥ 5%), interferon gamma (IFNγ)-related gene signature, gene expression profile, tumor mutational burden (TMB), and gene hyperamplification (HA) were analyzed for correlation with tislelizumab.

RESULTS

A moderate association was observed between PD-L1 TAP ≥ 5%, IFNγ gene signature, TMB-high and efficacy. A potential correlation between hyperamplification (HA +) and worse outcomes with programmed cell death protein 1 (PD-1) inhibition was identified. Hyperamplified genes were mainly enriched in cancer progression pathways, including cell cycle and RTK-RAS-PI3K pathways. Joint PD-L1 TAP ≥ 5% and lack of hyperamplification showed the most favorable benefit with an objective response rate of 29.4%, and median progression-free survival and overall survival of 4.1 and 14.7 months, respectively. Tumors with TAP ≥ 5% and HA - had inflamed immune signatures with increased immune cell infiltration, enhanced anti-tumor cytotoxic activity and antigen presentation signatures. Findings were validated in two independent gastric and gastrointestinal cancer cohorts treated with immune checkpoint inhibitors.

CONCLUSIONS

In GEA, PD-L1 positivity, IFNγ-related gene signature and TMB-high status were positively associated with tislelizumab clinical benefit, whereas HA was associated with worse clinical outcomes. Combining PD-L1 positivity and HA - may help identify patients more likely to benefit from PD-1 blockade.

Epigenome signature as an immunophenotype indicator prompts durable clinical immunotherapy benefits in lung adenocarcinoma

Intertumoral immune heterogeneity is a critical reason for distinct clinical benefits of immunotherapy in lung adenocarcinoma (LUAD). Tumor immunophenotype (immune 'Hot' or 'Cold') suggests immunological individual differences and potential clinical treatment guidelines. However, employing epigenome signatures to determine tumor immunophenotypes and responsive treatment is not well understood. To delineate the tumor immunophenotype and immune heterogeneity, we first distinguished the immune 'Hot' and 'Cold' tumors of LUAD based on five immune expression signatures. In terms of clinical presentation, the immune 'Hot' tumors usually had higher immunoactivity, lower disease stages and better survival outcomes than 'Cold' tumors. At the epigenome levels, we observed that distinct DNA methylation patterns between immunophenotypes were closely associated with LUAD development. Hence, we identified a set of five CpG sites as the immunophenotype-related methylation signature (iPMS) for tumor immunophenotyping and further confirmed its efficiency based on a machine learning framework. Furthermore, we found iPMS and immunophenotype-related immune checkpoints (IPCPs) could contribute to the risk of tumor progression, implying IPCP has the potential to be a novel immunotherapy blockade target. After further parsing of the role of iPMS-predicted immunophenotypes, we found immune 'Hot' was a protective factor leading to better survival outcomes when patients received the anti-PD-1/PD-L1 immunotherapy. And iPMS was also a well-performed signature (AUC = 0.752) for predicting the durable/nondurable clinical benefits. In summary, our study explored the role of epigenome signature in clinical tumor immunophenotyping. Utilizing iPMS to characterize tumor immunophenotypes will facilitate developing personalized epigenetic anticancer approaches.

Germline HLA-B evolutionary divergence influences the efficacy of immune checkpoint blockade therapy in gastrointestinal cancer

BACKGROUND

The human leukocyte antigen class I (HLA-I) genotype has been linked with differential immune responses to infectious disease and cancer. However, the clinical relevance of germline HLA-mediated immunity in gastrointestinal (GI) cancer remains elusive.

METHODS

This study retrospectively analyzed the genomic profiling data from 84 metastatic GI cancer patients treated with immune checkpoint blockade (ICB) recruited from Peking University Cancer Hospital (PUCH). A publicly available dataset from the Memorial Sloan Kettering (MSK) Cancer Center (MSK GI cohort) was employed as the validation cohort. For the PUCH cohort, we performed HLA genotyping by whole exome sequencing (WES) analysis on the peripheral blood samples from all patients. Tumor tissues from 76 patients were subjected to WES analysis and immune oncology-related RNA profiling. We studied the associations of two parameters of germline HLA as heterozygosity and evolutionary divergence (HED, a quantifiable measure of HLA-I evolution) with the clinical outcomes of patients in both cohorts.

RESULTS

Our data showed that neither HLA heterozygosity nor HED at the HLA-A/HLA-C locus correlated with the overall survival (OS) in the PUCH cohort. Interestingly, in both the PUCH and MSK GI cohorts, patients with high HLA-B HED showed a better OS compared with low HLA-B HED subgroup. Of note, a combinatorial biomarker of HLA-B HED and tumor mutational burden (TMB) may better stratify potential responders. Furthermore, patients with high HLA-B HED were characterized with a decreased prevalence of multiple driver gene mutations and an immune-inflamed phenotype.

CONCLUSIONS

Our results unveil how HLA-B evolutionary divergence influences the ICB response in patients with GI cancers, supporting its potential utility as a combinatorial biomarker together with TMB for patient stratification in the future.

Alterations in DNA damage response and repair genes as potential biomarkers for immune checkpoint blockade in gastrointestinal cancer

OBJECTIVE

Immune checkpoint inhibitors (ICIs) have achieved remarkable results in cancer treatments. However, there is no effective predictive biomarker for gastrointestinal (GI) cancer.

METHODS

We conducted integrative analyses of the genomic and survival data of ICI-treated GI cancer patients from the Memorial Sloan Kettering Cancer Center cohort (MSK-GI, n = 227), the Janjigian cohort (n = 40), and the Peking University Cancer Hospital & Institute cohort (PUCH, n = 80) to determine the possible associations between DNA damage response and repair (DDR) gene mutations and clinical outcomes. Data from The Cancer Genome Atlas database were analyzed to determine the possible correlations between DDR gene mutations and the tumor microenvironment.

RESULTS

In the MSK cohort, the presence of ≥ 2 DDR gene mutations was correlated with prolonged overall survival (OS). The Janjigian and PUCH cohorts further confirmed that subgroups with ≥ 2 DDR gene mutations displayed a prolonged OS and a higher durable clinical benefit. Furthermore, the DDR gene mutation load could be considered as an independent prognostic factor, and exhibited a potential predictive value for survival in GI cancer patients treated with ICIs. Mechanistically, we showed that the presence of ≥ 2 DDR gene mutations was correlated with higher levels of tumor mutation burden, neoantigen, and T cell infiltration.

CONCLUSIONS

The DDR gene mutation status was correlated with favorable clinical outcomes in GI cancer patients receiving ICIs, which could serve as a potential biomarker to guide patient selection for immunotherapy.