Intratumor heterogeneity: the hidden barrier to immunotherapy against MSI tumors from the perspective of IFN-γ signaling and tumor-infiltrating lymphocytes

Machine learning-based integration develops a multiple programmed cell death signature for predicting the clinical outcome and drug sensitivity in colorectal cancer

Tumorigenesis and treatment are closely associated with various programmed cell death (PCD) patterns. However, the coregulatory role of multiple PCD patterns in colorectal cancer (CRC) remains unknown. In this study, we developed a multiple PCD index (MPCDI) based on 19 PCD patterns using two machine learning algorithms for risk stratification, prognostic prediction, construction of nomograms, immune cell infiltration analysis, and chemotherapeutic drug sensitivity analysis. As a result, in the TCGA-COAD, GSE17536, and GSE29621 cohorts, the MPCDI can effectively distinguished survival outcomes in CRC patients and served as an independent factor for CRC patients. We then explored the immune infiltration landscape in two groups using the nine algorithms and found more overall immune infiltration in the high-MPCDI group. TIDE scores suggested that the increased immune evasion potential and immune checkpoint inhibition therapy may be less effective in the high-MPCDI group. Immunophenoscores indicated that anti-PD1, anti-cytotoxic T-lymphocyte associated antigen 4 (anti-CTLA4), and anti-PD1-CTLA4 combination therapies are less effective in the high-MPCDI group. In addition, the high-MPCDI group was more sensitive to AZD1332, Foretinib, and IGF1R_3801, and insensitive to AZD3759, AZD5438, AZD6482, Erlotinib, GSK591, IAP_5620, and Picolinici-acid, which suggests that the MPCDI can guide drug selection for CRC patients. As a new clinical classifier, the MPCDI can more accurately distinguish CRC patients who benefit from immunotherapy and develop personalized treatment strategies for CRC patients.

Computed Tomography-Based Intratumor Heterogeneity Predicts Response to Immunotherapy Plus Chemotherapy in Esophageal Squamous Cell Carcinoma

RATIONALE AND OBJECTIVES

This study explored the intratumor heterogeneity (ITH) of esophageal squamous cell carcinoma (ESCC) using computed tomography (CT) and investigated the value of CT-based ITH in predicting the response to immune checkpoint inhibitor (ICI) plus chemotherapy in patients with ESCC.

MATERIALS AND METHODS

This retrospective study included 416 patients with ESCC who received ICI plus chemotherapy at two independent hospitals between January 2019 and July 2022. Multiparametric CT features were extracted from ESCC lesions and screened using hierarchical clustering and dimensionality reduction algorithms. Logistic regression and machine learning models based on selected features were developed to predict treatment response and validated in separate datasets. ITH was quantified using the score calculated by the best-performing model and visualized through feature clustering and feature contribution heatmaps. A gene set enrichment analysis (GSEA) was performed to identify the biological pathways underlying the CT-based ITH.

RESULTS

The extreme gradient boosting model based on CT-derived ITH had higher discriminative power, with areas under the receiver operating characteristic curve of 0.864 (95% confidence interval [CI]: 0.774-0.954) and 0.796 (95% CI: 0.698-0.893) in the internal and external validation sets. The CT-based ITH pattern differed significantly between responding and non-responding patients. The GSEA indicated that CT-based ITH was associated with immunity-, keratinization-, and epidermal cell differentiation-related pathways.

CONCLUSION

CT-based ITH is an effective biomarker for identifying patients with ESCC who could benefit from ICI plus chemotherapy. Immunity-, keratinization-, and epidermal cell differentiation-related pathways may influence the patient's response to ICI plus chemotherapy.

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.

A retrospective analysis of the clinicopathological features and prognostic value of MAPK12 protein expression in diffuse large B-cell lymphoma

PURPOSE

Mitogen-activated protein kinase 12 (MAPK12), also known as p38γ, is a member of the p38 MAPK family and plays a crucial role in tumor occurrence and invasion. However, there is still uncertainty regarding MAPK12 involvement in diffuse large B-cell lymphoma (DLBCL).

METHODS

Our study investigated the expression of MAPK12 mRNA in various types of cancer using bioinformatic analysis. Furthermore, we performed immunohistochemistry (IHC) to detect the expression of MAPK12 in patients with DLBCL and compared clinical indicators and survival rates.

RESULTS

We found that the high expression rate of MAPK12 was 43.1% in DLBCL patients. Several clinical indicators, including IPI scores, Hans classifications, LDH levels, and Ki-67 expression were closely associated with MAPK12 expression. Survival analysis revealed that higher expression of MAPK12 was significantly correlated with shorter progression-free survival (PFS) and overall survival (OS) in DLBCL patients. In addition, both univariate and multivariate analyses revealed IPI score, MAPK12 expression, and rituximab use as the independent OS risk factors (P < 0.05). To explore the functional role of MAPK12 in DLBCL, weighted gene co-expression network analysis (WGCNA) and gene ontology (GO) were used to confirm the involvement of MAPK12 in the regulation of type II interferon production, positive regulation of lymphocyte proliferation, and other related biological processes.

CONCLUSION

DLBCL patients have poor prognoses when MAPK12 levels are high, which is expected to be a therapeutic target and prognostic factor.

Plasma proteome profiling reveals dynamic of cholesterol marker after dual blocker therapy

Dual blocker therapy (DBT) has the enhanced antitumor benefits than the monotherapy. Yet, few effective biomarkers are developed to monitor the therapy response. Herein, we investigate the DBT longitudinal plasma proteome profiling including 113 longitudinal samples from 22 patients who received anti-PD1 and anti-CTLA4 DBT therapy. The results show the immune response and cholesterol metabolism are upregulated after the first DBT cycle. Notably, the cholesterol metabolism is activated in the disease non-progressive group (DNP) during the therapy. Correspondingly, the clinical indicator prealbumin (PA), free triiodothyronine (FT3) and triiodothyronine (T3) show significantly positive association with the cholesterol metabolism. Furthermore, by integrating proteome and radiology approach, we observe the high-density lipoprotein partial remodeling are activated in DNP group and identify a candidate biomarker APOC3 that can reflect DBT response. Above, we establish a machine learning model to predict the DBT response and the model performance is validated by an independent cohort with balanced accuracy is 0.96. Thus, the plasma proteome profiling strategy evaluates the alteration of cholesterol metabolism and identifies a panel of biomarkers in DBT.

Machine learning unveils immune-related signature in multicenter glioma studies

In glioma molecular subtyping, existing biomarkers are limited, prompting the development of new ones. We present a multicenter study-derived consensus immune-related and prognostic gene signature (CIPS) using an optimal risk score model and 101 algorithms. CIPS, an independent risk factor, showed stable and powerful predictive performance for overall and progression-free survival, surpassing traditional clinical variables. The risk score correlated significantly with the immune microenvironment, indicating potential sensitivity to immunotherapy. High-risk groups exhibited distinct chemotherapy drug sensitivity. Seven signature genes, including IGFBP2 and TNFRSF12A, were validated by qRT-PCR, with higher expression in tumors and prognostic relevance. TNFRSF12A, upregulated in GBM, demonstrated inhibitory effects on glioma cell proliferation, migration, and invasion. CIPS emerges as a robust tool for enhancing individual glioma patient outcomes, while IGFBP2 and TNFRSF12A pose as promising tumor markers and therapeutic targets.

Versican Associates with Tumor Immune Phenotype and Limits T-cell Trafficking via Chondroitin Sulfate

Immunotherapies for cancers of epithelial origin have limited efficacy, and a growing body of evidence links the composition of extracellular matrix (ECM) with the likelihood of a favorable response to treatment. The ECM may be considered an immunologic barrier, restricting the localization of cytotoxic immune cells to stromal areas and inhibiting their contact with tumor cells. Identifying ECM components of this immunologic barrier could provide targets that whether degraded in situ may support antitumor immunity and improve immunotherapy response. Using a library of primary triple-negative breast cancer tissues, we correlated CD8+ T-cell tumor contact with ECM composition and identified a proteoglycan, versican (VCAN), as a putative member of the immunologic barrier. Our analysis reveals that CD8+ T-cell contact with tumor associates with the location of VCAN expression, the specific glycovariant of VCAN [defined through the pattern of posttranslational attachments of glycosaminoglycans (GAG)], and the cell types that produce the variant. In functional studies, the isomers of chondroitin sulfate presented on VCAN have opposing roles being either supportive or inhibiting of T-cell trafficking, and removal of the GAGs ameliorates these effects on T-cell trafficking. Overall, we conclude that VCAN can either support or inhibit T-cell trafficking within the tumor microenvironment depending on the pattern of GAGs present, and that VCAN is a major component of the ECM immunologic barrier that defines the type of response to immunotherapy.

SIGNIFICANCE

The response to immunotherapy has been poor toward solid tumors despite immune cells infiltrating into the tumor. The ECM has been associated with impacting T-cell infiltration toward the tumor and in this article we have identified VCAN and its structural modification, chondroitin sulfate as having a key role in T-cell invasion.

Irradiated engineered tumor cell-derived microparticles remodel the tumor immune microenvironment and enhance antitumor immunity

Radiotherapy (RT), administered to roughly half of all cancer patients, occupies a crucial role in the landscape of cancer treatment. However, expanding the clinical indications of RT remains challenging. Inspired by the radiation-induced bystander effect (RIBE), we used the mediators of RIBE to mimic RT. Specifically, we discovered that irradiated tumor cell-released microparticles (RT-MPs) mediated the RIBE and had immune activation effects. To further boost the immune activation effect of RT-MPs to achieve cancer remission, even in advanced stages, we engineered RT-MPs with different cytokine and chemokine combinations by modifying their production method. After comparing the therapeutic effect of the engineered RT-MPs in vitro and in vivo, we demonstrated that tIL-15/tCCL19-RT-MPs effectively activated antitumor immune responses, significantly prolonged the survival of mice with malignant pleural effusion (MPE), and even achieved complete cancer remission. When tIL-15/tCCL19-RT-MPs were combined with PD-1 monoclonal antibody (mAb), a cure rate of up to 60% was achieved. This combination therapy relied on the activation of CD8+ T cells and macrophages, resulting in the inhibition of tumor growth and the establishment of immunological memory against tumor cells. Hence, our research may provide an alternative and promising strategy for cancers that are not amenable to conventional RT.

Direct visualization of immune status for tumor-infiltrating lymphocytes by rolling circle amplification

The immune status of tumor-infiltrating lymphocytes (TILs) is essential for the effectiveness of cancer immunotherapies. However, due to the diversity of immune status in TILs, cellular heterogeneity, and the applicability to the clinic, it is still lacking effective strategies to meet clinical needs. We developed a novel immuno-recognition-induced method based on rolling circle amplification (RCA), namely immunoRCA, to in situ visualize the immune status of TILs in actual clinical samples. This developed immunoRCA method, in which, feature mRNAs were used as the biomarkers for the immune status of TILs, has a low fluorescence background, high sensitivity, and specificity. The immunoRCA was able to efficiently evaluate the immune status of CD8+ T cells regulated by activating or inhibiting factors, track the T cell type and immune status during in vitro expansion, and in situ visualize the number, location, and immune status of TILs in clinical specimens.

Tumor Microenvironment-Responsive Nanoparticles Amplifying STING Signaling Pathway for Cancer Immunotherapy

Insufficient activation of the stimulator of interferon genes (STING) signaling pathway and profoundly immunosuppressive microenvironment largely limits the effect of cancer immunotherapy. Herein, tumor microenvironment (TME)-responsive nanoparticles (PMM NPs) are exploited that simultaneously harness STING and Toll-like receptor 4 (TLR4) to augment STING activation via TLR4-mediated nuclear factor-kappa B signaling pathway stimulation, leading to the increased secretion of type I interferons (i.e., 4.0-fold enhancement of IFN-β) and pro-inflammatory cytokines to promote a specific T cell immune response. Moreover, PMM NPs relieve the immunosuppression of the TME by decreasing the percentage of regulatory T cells, and polarizing M2 macrophages to the M1 type, thus creating an immune-supportive TME to unleash a cascade adaptive immune response. Combined with an anti-PD-1 antibody, synergistic efficacy is achieved in both inflamed colorectal cancer and noninflamed metastatic breast tumor models. Moreover, rechallenging tumor-free animals with homotypic cells induced complete tumor rejection, indicating the generation of systemic antitumor memory. These TME-responsive nanoparticles may open a new avenue to achieve the spatiotemporal orchestration of STING activation, providing a promising clinical candidate for next-generation cancer immunotherapy.

The tertiary lymphoid structure-related signature identified PTGDS in regulating PD-L1 and promoting the proliferation and migration of glioblastoma

Background

Tertiary lymphoid structure (TLS) is a unique organ that carries out tumor cell elimination at tumor sites. It is continuously stimulated by inflammatory tumor signals and has been found to augment immunotherapy response. However, the detailed mechanisms behind it still need to be defined.

Methods

To explore and grasp the whole picture of TLS from a pan-cancer view, we collected nine TLS-related genes from previous studies. We performed a comprehensive analysis of 9637 samples across 33 tumor types accessed from The Cancer Genome Atlas (TCGA) database. EdU, Transwell, and flow cytometry were performed on the feature gene PTGDS in U251 cells. The regulatory role of PTGDS on PD-L1 expression and macrophage polarization was verified.

Results

Alteration analysis showed that mutations of TLS-related genes were widespread and relatively high. Clustering analysis based on the expression of these nine genes obtained two distinct clusters, with high EIF1AY and PTGDS in cluster 2 and better overall survival in cluster 1. To distinguish the two clusters, we utilized six machine learning algorithms and filtrated EIF1AY, PTGDS, SKAP1, and RBP5 as the characteristic genes, among which the former two genes were proved to be hazardous. PTGDS was found to regulate PD-L1 expression and also promoted the proliferation and migration of U251 cells. The knockdown of PTGDS could reduce the migration of macrophages and inhibit the polarization of macrophages into M2-phenotype. In addition, we established a TLS score to demonstrate patients' TLS activity. The low TLS-score group overlapped with cluster 1 and displayed a better prognosis. Besides, the low TLS-score group was related to better immunotherapy responses. The HE staining of histopathological sections confirmed that the low TLS-score group exhibited higher infiltration of immune cells.

Conclusion

This study reveals broad molecular, tumorigenic, and immunogenic signatures for further functional and therapeutic studies of tertiary lymphoid structure. The TLS score we established effectively predicted immunotherapy response and patients' survival. Its future application and combination await more research.

Single-cell dissection reveals the role of aggrephagy patterns in tumor microenvironment components aiding predicting prognosis and immunotherapy on lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the leading malignant cancers. Aggrephagy plays a critical role in key genetic events for various cancers; yet, how aggrephagy functions within the tumor microenvironment (TME) in LUAD remains to be elucidated.

METHODS

In this study, by sequential non-negative matrix factorization (NMF) algorithm, pseudotime analysis, cell-cell interaction analysis, and SCENIC analysis, we have shown that aggrephagy genes demonstrated various patterns among different cell types in LUAD TME. LUAD and Immunotherapy cohorts from public repository were used to determine the prognosis and immune response of aggrephagy TME subtypes. The aggrephagy-deprived prognostic score (ADPS) was quantified based on machine learning algorithms.

RESULTS

The cancer-associated fibroblasts (CAFs), tumor-associated macrophages (TAMs), and CD8+ T cells have various aggrephagy patterns, which enhance the intensity of intercellular communication and transcription factor activation. Furthermore, based on the signatures of the newly defined aggrephagy cell subtypes and expression profiles of large cohorts in LUAD patients, we determine that DYNC1I2+CAF-C1, DYNLL1+CAF-C2, PARK7+CAF-C3, VIM+Mac-C1, PARK7+Mac-C2, VIM+CD8+T_cells-C1, UBA52+CD8+T_cells-C2, TUBA4A+CD8+T_ cells-C3, and TUBA1A+CD8+T_cells-C4 are crucial prognostic factors for LUAD patients. The developed ADPS could predict survival outcomes and immunotherapeutic response across ten cohorts (n = 1838), and patients with low ADPS owned a better prognosis, lower genomic alterations, and are more sensitive to immunotherapy. Meanwhile, based on PRISM, CTRP, and CMAP databases, PLK inhibitor BI-2536, may be a potential agent for patients with high ADPS.

CONCLUSIONS

Taken together, our novel and systematic single-cell analysis has revealed the unique role of aggrephagy in remodeling the TME of LUAD. As a newly demonstrated biomarker, the ADPS facilitates the clinical management and individualized treatment of LUAD.

Evaluation of an eight marker-panel including long mononucleotide repeat markers to detect microsatellite instability in colorectal, gastric, and endometrial cancers

BACKGROUND

Accurate determination of microsatellite instability (MSI) status is critical for optimal treatment in cancer patients. Conventional MSI markers can sometimes display subtle shifts that are difficult to interpret, especially in non-colorectal cases. We evaluated an experimental eight marker-panel including long mononucleotide repeat (LMR) markers for detection of MSI.

METHODS

The eight marker-panel was comprised of five conventional markers (BAT-25, BAT-26, NR-21, NR-24, and NR-27) and three LMR markers (BAT-52, BAT-59 and BAT-62). MSI testing was performed against 300 specimens of colorectal, gastric, and endometrial cancers through PCR followed by capillary electrophoresis length analysis.

RESULTS

The MSI testing with eight marker-panel showed 99.3% (295/297) concordance with IHC analysis excluding 3 MMR-focal deficient cases. The sensitivity of BAT-59 and BAT-62 was higher than or comparable to that of conventional markers in gastric and endometrial cancer. The mean shift size was larger in LMR markers compared to conventional markers for gastric and endometrial cancers.

CONCLUSIONS

The MSI testing with eight maker-panel showed comparable performance with IHC analysis. The LMR markers, especially BAT-59 and BAT-62, showed high sensitivity and large shifts which can contribute to increased confidence in MSI classification, especially in gastric and endometrial cancers. Further study is needed with large number of samples for the validation of these LMR markers.

Personalised neoantigen-based therapy in colorectal cancer

Colorectal cancer (CRC) has become one of the most common tumours with high morbidity, mortality and distinctive evolution mechanism. The neoantigens arising from the somatic mutations have become considerable treatment targets in the management of CRC. As cancer-specific aberrant peptides, neoantigens can trigger the robust host immune response and exert anti-tumour effects while minimising the emergence of adverse events commonly associated with alternative therapeutic regimens. In this review, we summarised the mechanism, generation, identification and prognostic significance of neoantigens, as well as therapeutic strategies challenges of neoantigen-based therapy in CRC. The evidence suggests that the establishment of personalised neoantigen-based therapy holds great promise as an effective treatment approach for patients with CRC.

Tumor-agnostic drug development in dMMR/MSI-H solid tumors

Mismatch repair deficiency (dMMR) or microsatellite instability-high (MSI-H) represents a distinct phenotype among solid tumors characterized by frequent frameshift mutations resulting in the generation of neoantigens that are highly immunogenic. Seminal studies identified that dMMR/MSI-H tumors are exquisitely sensitive to immune checkpoint inhibitors, which has dramatically improved outcomes for patients harboring dMMR/MSI-H tumors. Nevertheless, many patients develop resistance to single-agent immune checkpoint blockade, prompting the need for improved therapeutic options for this patient population. In this review, we highlight key studies examining the efficacy of PD1 inhibitors in the metastatic and neoadjuvant setting for patients with dMMR/MSI-H tumors, describe resistance mechanisms to immune checkpoint blockade, and discuss novel treatment approaches that are currently under investigation for dMMR/MSI-H tumors.

Current Status in Rechallenge of Immunotherapy

The treatment of malignant tumors has entered the era of immunotherapy, and immune checkpoint inhibitors (ICIs) have brought significant benefits to patients. However, some patients are required to discontinue treatment with ICIs owing to factors such as disease progression and intolerable side effects. Faced with limited subsequent treatment options and complex medical needs, we searched PubMed, Embase, Cochrane library, and the NIH clinical trials database and found that ICI rechallenge could be a relevant clinical strategy. The factors that could affect the rechallenge efficacy include the patients' characteristics, therapeutic strategy selection, and the timing of treatment. Multiple factors are used to identify target population, of which clinical features and PD-L1 expression are more potential. Both single ICI rechallenge and combination therapy may have survival benefits. Patients who have tolerated initial immunotherapy well could undergo ICI rechallenge, while patients who have experienced grade 3 or higher immune-related adverse events should be carefully assessed prior to rechallenge. Interventions and the interval between two courses of ICI will clearly have an impact on the efficacy of subsequent treatment. Preliminary data evaluation supports further investigation on ICI rechallenge to identify the factors that could contribute to its efficacy.

Clinical atlas of rectal cancer highlights the barriers and insufficient interventions underlying the unfavorable outcomes in older patients

Background

Aging confers an increased risk of developing cancer, and the global burden of cancer is cumulating as human longevity increases. Providing adequate care for old patients with rectal cancer is challenging and complex.

Method

A total of 428 and 44,788 patients diagnosed with non-metastatic rectal cancer from a referral tertiary care center (SYSU cohort) and the Surveillance Epidemiology and End Results database (SEER cohort) were included. Patients were categorized into old (over 65 years) and young (aged 50-65 years) groups. An age-specific clinical atlas of rectal cancer was generated, including the demographic and clinicopathological features, molecular profiles, treatment strategies, and clinical outcomes.

Results

Old and young patients were similar in clinicopathological risk factors and molecular features, including TNM stage, tumor location, tumor differentiation, tumor morphology, lymphovascular invasion, and perineural invasion. However, old patients had significantly worse nutritional status and more comorbidities than young patients. In addition, old age was independently associated with less systemic cancer treatment (adjusted odds ratio 0.294 [95% CI 0.184-0.463, P < 0.001]). We found that old patients had significantly worse overall survival (OS) outcomes in both SYSU (P < 0.001) and SEER (P < 0.001) cohorts. Moreover, the death and recurrence risk of old patients in the subgroup not receiving chemo/radiotherapy (P < 0.001 for OS, and P = 0.046 for time to recurrence [TTR]) reverted into no significant risk in the subgroup receiving chemo/radiotherapy.

Conclusions

Although old patients had similar tumor features to young patients, they had unfavorable survival outcomes associated with insufficient cancer care from old age. Specific trials with comprehensive geriatric assessment for old patients are needed to identify the optimal treatment regimens and improve unmet cancer care.

Study registration

The study was registered on the research registry with the identifier of researchregistry 7635.

Predictive value of intratumoral-metabolic heterogeneity derived from 18F-FDG PET/CT in distinguishing microsatellite instability status of colorectal carcinoma

Purpose/background

Microsatellite instability (MSI) status is a significant biomarker for the response to immune checkpoint inhibitors, response to 5-fluorouracil-based adjuvant chemotherapy, and prognosis in colorectal carcinoma (CRC). This study investigated the predictive value of intratumoral-metabolic heterogeneity (IMH) and conventional metabolic parameters derived from 18F-FDG PET/CT for MSI in patients with stage I-III CRC.

Methods

This study was a retrospective analysis of 152 CRC patients with pathologically proven MSI who underwent 18F-FDG PET/CT examination from January 2016 to May 2022. Intratumoral-metabolic heterogeneity (including heterogeneity index [HI] and heterogeneity factor [HF]) and conventional metabolic parameters (standardized uptake value [SUV], metabolic tumor volume [MTV], and total lesion glycolysis [TLG]) of the primary lesions were determined. MTV and SUVmean were calculated on the basis of the percentage threshold of SUVs at 30%-70%. TLG, HI, and HF were obtained on the basis of the above corresponding thresholds. MSI was determined by immunohistochemical evaluation. Differences in clinicopathologic and various metabolic parameters between MSI-High (MSI-H) and microsatellite stability (MSS) groups were assessed. Potential risk factors for MSI were assessed by logistic regression analyses and used for construction of the mathematical model. Area under the curve (AUC) were used to evaluate the predictive ability of factors for MSI.

Results

This study included 88 patients with CRC in stages I-III, including 19 (21.6%) patients with MSI-H and 69 (78.4%) patients with MSS. Poor differentiation, mucinous component, and various metabolic parameters including MTV30%, MTV40%, MTV50%, and MTV60%, as well as HI50%, HI60%, HI70%, and HF in the MSI-H group were significantly higher than those in the MSS group (all P < 0.05). In multivariate logistic regression analyses, post-standardized HI60% by Z-score (P = 0.037, OR: 2.107) and mucinous component (P < 0.001, OR:11.394) were independently correlated with MSI. AUC of HI60% and our model of the HI60% + mucinous component was 0.685 and 0.850, respectively (P = 0.019), and the AUC of HI30% in predicting the mucinous component was 0.663.

Conclusions

Intratumoral-metabolic heterogeneity derived from 18F-FDG PET/CT was higher in MSI-H CRC and predicted MSI in stage I-III CRC patients preoperatively. HI60% and mucinous component were independent risk factors for MSI. These findings provide new methods to predict the MSI and mucinous component for patients with CRC.

Patient-derived xenograft models in cancer therapy: technologies and applications

Patient-derived xenograft (PDX) models, in which tumor tissues from patients are implanted into immunocompromised or humanized mice, have shown superiority in recapitulating the characteristics of cancer, such as the spatial structure of cancer and the intratumor heterogeneity of cancer. Moreover, PDX models retain the genomic features of patients across different stages, subtypes, and diversified treatment backgrounds. Optimized PDX engraftment procedures and modern technologies such as multi-omics and deep learning have enabled a more comprehensive depiction of the PDX molecular landscape and boosted the utilization of PDX models. These irreplaceable advantages make PDX models an ideal choice in cancer treatment studies, such as preclinical trials of novel drugs, validating novel drug combinations, screening drug-sensitive patients, and exploring drug resistance mechanisms. In this review, we gave an overview of the history of PDX models and the process of PDX model establishment. Subsequently, the review presents the strengths and weaknesses of PDX models and highlights the integration of novel technologies in PDX model research. Finally, we delineated the broad application of PDX models in chemotherapy, targeted therapy, immunotherapy, and other novel therapies.

Use of the prognostic nutrition index as a predictive biomarker in small-cell lung cancer patients undergoing immune checkpoint inhibitor treatment in the Chinese alpine region

Background

Whether the prognostic nutritional index (PNI), which is suggested to reflect systemic inflammation and nutritional status of patients, could be used as an effective prognostic factor for small-cell lung cancer (SCLC) has not yet been clarified. The purpose of this study was to verify the prognostic value of the PNI in SCLC patients treated with programmed cell death ligand-1/programmed cell death 1 (PD-L1/PD-1) inhibitors in the alpine region of China.

Methods

SCLC patients treated with PD-L1/PD-1 inhibitors monotherapy or combined with chemotherapy between March 2017 and May 2020 were included. Based on the values of serum albumin and total lymphocyte count, the study population was divided into two groups: high and low PNI. The Kaplan-Meier method was used to compute the median survival time and the log-rank test was used to compare the two groups. To evaluate the prognostic value of the PNI, univariable and multivariable analyses of progression-free survival (PFS) and overall survival (OS) were performed. The correlations between PNI and DCR or ORR were calculated by Point biserial correlation analysis.

Results

One hundred and forty patients were included in this study, of which, 60.0% were high PNI (PNI &gt; 49.43) and 40.0% were low PNI (PNI ≤ 49.43). Results indicated that the high PNI group had better PFS and OS than the low PNI group in the patients who received PD-L1/PD-1 inhibitors monotherapy (median PFS: 11.0 vs. 4.8 months, p &lt; 0.001 and median OS: 18.5 vs. 11.0 months, p = 0.004). Similarly, better PFS and OS were associated with an increase in PNI level in the patients who accepted PD-L1/PD-1 inhibitors combined with chemotherapy (median PFS: 11.0 vs. 5.3 months, p &lt; 0.001 and median OS: 17.9 vs. 12.6 months, p = 0.005). Multivariate Cox-regression model showed that high PNI was significantly related to better PFS and OS in patients who accepted PD-L1/PD-1 inhibitors monotherapy or combined with chemotherapy (PD-L1/PD-1 inhibitors monotherapy: PFS: HR = 0.23, 95% CI: 0.10–0.52, p &lt; 0.001 and OS: HR = 0.13, 95% CI: 0.03–0.55, p = 0.006; PD-L1/PD-1 inhibitors combined with chemotherapy: PFS: HR = 0.34, 95% CI: 0.19–0.61, p &lt; 0.001 and OS: HR = 0.53, 95% CI: 0.29–0.97, p = 0.040, respectively). Additionally, Point biserial correlation analysis between PNI and disease control rate (DCR) showed that PNI status was positively correlated with DCR in SCLC patients receiving PD-L1/PD-1 inhibitors or combined with chemotherapy (r = 0.351, p &lt; 0.001; r = 0.285, p &lt; 0.001, respectively).

Concussions

PNI may be a promising biomarker of treatment efficacy and prognosis in SCLC patients treated with PD-L1/PD-1 inhibitors in the alpine region of China.

Promise of dostarlimab in cancer therapy: Advancements and cross-talk considerations

In recent years, immunotherapy for cancer treatment using monoclonal antibodies has shown clinical success, particularly with programmed cell death protein 1 (PD-1) and its ligand programmed death-ligand 1 (PD-L1). Dostarlimab, an immune checkpoint inhibitor, interacts with adaptive immunity by binding to human PD-1, inhibiting PD-L1 and PD-L2 interactions, and cross-talk with adaptive immunity. Recent clinical trials have shown that dostarlimab is effective in treating mismatch repair deficiency (dMMR) in endometrial cancer patients, leading to its approval in the United States and the European Union in 2021. This article provides a comprehensive overview of dostarlimab, its therapeutic ability, and the different indications for which it is being used. Dostarlimab could serve as a potential alternative to many cancer treatments that frequently have severe consequences on patients' quality of life. Teaser The comprehensive story behind dostarlimab is how it cured all 18 cancer patients who took part in the experimental clinical trial, ultimately leading to its approval by the US FDA.

An exploration of gastric cancer with heterogeneous mismatch repair status

Survival benefits or symptom alleviation from immune checkpoint blockade therapy can be seen in microsatellite instability-high (MSI-H) cases. However, genetic heterogeneity within a specific subgroup of MSI-H tumors may be associated with poor response and prognosis. We investigated the molecular changes and microsatellite status of the cases with heterogeneous MMR protein staining by polymerase chain reaction (PCR) and next-generation sequencing (NGS). Data from 3723 patients with gastric cancer were retrospectively analyzed to determine the mismatch repair (MMR) status by performing immunohistochemical staining of four major MMR proteins (MLH1, PMS2, MSH2, and MSH6). When heterogeneous MMR protein staining result was positive, PCR and NGS were performed. Heterogeneous MMR protein staining was observed in 12 cases. In microsatellite stable (MSS) cases, TP53 mutation appeared to accompany heterogeneous staining (HS) of MLH1. However, TP53 variation was not observed with MSI-H occurrence. Cases showing heterogeneous MSH6 protein staining revealed MSH6 mutations. Some cases with the same MMR protein staining set had varying MSI results. In one case whose primary and metastatic foci presented MLH1-HS and PMS2-HS, the microsatellite status was classified as MSS and MSI-H, respectively. Moreover, HS was also found in multiple biopsies and surgical specimens. This study found a preliminary relationship between heterogeneously stained MSH6 or MLH1 proteins and their gene mutations, as well as between MSI-H/TP53 - and MSS/TP53 + tumors. The microsatellite status of patients with heterogeneous MMR protein staining is unpredictable. Given the heterogeneity of mismatch repair, microsatellite status should be assessed for all specimens if sufficient specimens can be obtained.

An artificial intelligence network-guided signature for predicting outcome and immunotherapy response in lung adenocarcinoma patients based on 26 machine learning algorithms

The immune cells play an increasingly vital role in influencing the proliferation, progression, and metastasis of lung adenocarcinoma (LUAD) cells. However, the potential of immune cells' specific genes-based model remains largely unknown. In the current study, by analysing single-cell RNA sequencing (scRNA-seq) data and bulk RNA sequencing data, the tumour-infiltrating immune cell (TIIC) associated signature was developed based on a total of 26 machine learning (ML) algorithms. As a result, the TIIC signature score could predict survival outcomes of LUAD patients across five independent datasets. The TIIC signature score showed superior performance to 168 previously established signatures in LUAD. Moreover, the TIIC signature score developed by the immunofluorescence staining of the tissue array of LUAD patients showed a prognostic value. Our research revealed a solid connection between TIIC signature score and tumour immunity as well as metabolism. Additionally, it has been discovered that the TIIC signature score can forecast genomic change, chemotherapeutic drug susceptibility, and-most significantly-immunotherapeutic response. As a newly demonstrated biomarker, the TIIC signature score facilitated the selection of the LUAD population who would benefit from future clinical stratification.

Exploiting RIG-I-like receptor pathway for cancer immunotherapy

RIG-I-like receptors (RLRs) are intracellular pattern recognition receptors that detect viral or bacterial infection and induce host innate immune responses. The RLRs family comprises retinoic acid-inducible gene 1 (RIG-I), melanoma differentiation-associated gene 5 (MDA5) and laboratory of genetics and physiology 2 (LGP2) that have distinctive features. These receptors not only recognize RNA intermediates from viruses and bacteria, but also interact with endogenous RNA such as the mislocalized mitochondrial RNA, the aberrantly reactivated repetitive or transposable elements in the human genome. Evasion of RLRs-mediated immune response may lead to sustained infection, defective host immunity and carcinogenesis. Therapeutic targeting RLRs may not only provoke anti-infection effects, but also induce anticancer immunity or sensitize "immune-cold" tumors to immune checkpoint blockade. In this review, we summarize the current knowledge of RLRs signaling and discuss the rationale for therapeutic targeting RLRs in cancer. We describe how RLRs can be activated by synthetic RNA, oncolytic viruses, viral mimicry and radio-chemotherapy, and how the RNA agonists of RLRs can be systemically delivered in vivo. The integration of RLRs agonism with RNA interference or CAR-T cells provides new dimensions that complement cancer immunotherapy. Moreover, we update the progress of recent clinical trials for cancer therapy involving RLRs activation and immune modulation. Further studies of the mechanisms underlying RLRs signaling will shed new light on the development of cancer therapeutics. Manipulation of RLRs signaling represents an opportunity for clinically relevant cancer therapy. Addressing the challenges in this field will help develop future generations of cancer immunotherapy.

Pan-Cancer Analysis of the TRP Family, Especially TRPV4 and TRPC4, and Its Expression Correlated with Prognosis, Tumor Microenvironment, and Treatment Sensitivity

BACKGROUND

Transient receptor potential (TRP) channels are involved in various physiological, pathological, and tumorigenesis-related processes. However, only a few studies have comprehensively analyzed TRP family members and their association with prognosis and tumor microenvironment (TME) in various cancers. Thus, in this study, we focused on TRP channels in pan-cancer and screened two typical TRP channels, TRPV4 and TRPC4, as examples.

METHODS

Based on the latest public databases, we evaluated the expression level and prognostic value of TRP family genes in pan-cancer tissues via various bioinformatic analytical methods, and investigated the relationship between the expression of TRP family genes with TME, stemness score, immune subtype, drug sensitivity, and immunotherapy outcome in pan-cancer tissues.

RESULTS

Pan-cancer analysis revealed that the TRP family genes were differentially expressed in tumor and para-carcinoma tissues. A significant correlation existed between the expression of TRP family genes and prognosis. The expression of TRP family genes was significantly correlated with stromal, immune, RNA stemness, and DNA stemness scores in pan-cancer tissues. Our results indicated that the expression of TRP family genes correlated with the sensitivity to various drugs including PLX-4720, SB-590885, and HYPOTHEMYCIN, immunotherapy outcome, and immune-activation-related genes. Immunohistochemical analysis revealed significant differential expression of TRPV4 in bladder and para-carcinoma tissues.

CONCLUSIONS

Our study elucidated the possible role of TRP family genes in cancer progression and provided insights for further studies on TRP family genes as potential pan-cancer targets to develop diagnostic and therapeutic strategies.

Towards a consensus definition of immune exclusion in cancer

Background

The immune cell topography of solid tumors has been increasingly recognized as an important predictive factor for progression of disease and response to immunotherapy. The distribution pattern of immune cells in solid tumors is commonly classified into three categories - namely, "Immune inflamed", "Immune desert" and "Immune excluded" - which, to some degree, connect immune cell presence and positioning within the tumor microenvironment to anti-tumor activity.

Materials and methods

In this review, we look at the ways immune exclusion has been defined in published literature and identify opportunities to develop consistent, quantifiable definitions, which in turn, will allow better determination of the underlying mechanisms that span cancer types and, ultimately, aid in the development of treatments to target these mechanisms.

Results

The definitions of tumor immune phenotypes, especially immune exclusion, have largely been conceptual. The existing literature lacks in consistency when it comes to practically defining immune exclusion, and there is no consensus on a definition. Majority of the definitions use somewhat arbitrary cut-offs in an attempt to place each tumor into a distinct phenotypic category. Tumor heterogeneity is often not accounted for, which limits the practical application of a definition.

Conclusions

We have identified two key issues in existing definitions of immune exclusion, establishing clinically relevant cut-offs within the spectrum of immune cell infiltration as well as tumor heterogeneity. We propose an approach to overcome these limitations, by reporting the degree of immune cell infiltration, tying cut-offs to clinically meaningful outcome measures, maximizing the number of regions of a tumor that are analyzed and reporting the degree of heterogeneity. This will allow for a consensus practical definition for operationalizing this categorization into clinical trial and signal-seeking endpoints.

Prognostic and Immunological Implications of FAM72A in Pan-Cancer and Functional Validations

The family with sequence similarity 72 Member A (FAM72A) is overexpressed in several types of cancer. However, its contributions to tumorigenesis remain largely unknown. Based on The Cancer Genome Atlas (TCGA) database, FAM72A was upregulated across 33 types of cancer. Accordingly, high levels of FAM72A predicted inferior outcomes in half of the cancer types using survival analysis (the Kaplan-Meier curve and univariate Cox regression model). Receiver operating characteristic (ROC) analysis demonstrated that FAM72A showed high accuracy in distinguishing cancerous tissues from normal ones. FAM72A was correlated with immune and stromal scores and immune cell infiltrations in various tumors. Moreover, FAM72A was also associated with tumor mutation burden (TMB), microsatellite instability (MSI), and immune checkpoint genes. Immunophenoscore (IPS) further validated that the FAM72A^low tumor showed high immunogenicity and tended to respond to anti-PD1/PDL1/PDL2, anti-CTLA4 treatment, and combined immunotherapies. We also investigated the functional role of FAM72A in lung adenocarcinoma (LUAD). In vitro studies demonstrated that the ectopic expression of FAM72A accelerated the proliferation and migration of NSCLC cells, whereas silencing FAM72A showed the opposite effects on them. In short, FAM72A had prognostic potential and correlated with tumor immunogenicity in various tumors. Functional analysis indicated that FAM72A is an oncogene in LUAD.

Clinicopathological characteristics of high microsatellite instability/mismatch repair-deficient colorectal cancer: A narrative review

Colorectal cancers (CRCs) with high microsatellite instability (MSI-H) and deficient mismatch repair (dMMR) show molecular and clinicopathological characteristics that differ from those of proficient mismatch repair/microsatellite stable CRCs. Despite the importance of MSI-H/dMMR status in clinical decision making, the testing rates for MSI and MMR in clinical practice remain low, even in high-risk populations. Additionally, the real-world prevalence of MSI-H/dMMR CRC may be lower than that reported in the literature. Insufficient MSI and MMR testing fails to identify patients with MSI-H/dMMR CRC, who could benefit from immunotherapy. In this article, we describe the current knowledge of the clinicopathological features, molecular landscape, and radiomic characteristics of MSI-H/dMMR CRCs. A better understanding of the importance of MMR/MSI status in the clinical characteristics and prognosis of CRC may help increase the rates of MMR/MSI testing and guide the development of more effective therapies based on the unique features of these tumors.

Targeting toll-like receptor 7/8 for immunotherapy: recent advances and prospectives

Toll-like receptors (TLRs) are a large family of proteins that are expressed in immune cells and various tumor cells. TLR7/8 are located in the intracellular endosomes, participate in tumor immune surveillance and play different roles in tumor growth. Activation of TLRs 7 and 8 triggers induction of a Th1 type innate immune response in the highly sophisticated process of innate immunity signaling with the recent research advances involving the small molecule activation of TLR 7 and 8. The wide range of expression and clinical significance of TLR7/TLR8 in different kinds of cancers have been extensively explored. TLR7/TLR8 can be used as novel diagnostic biomarkers, progression and prognostic indicators, and immunotherapeutic targets for various tumors. Although the mechanism of action of TLR7/8 in cancer immunotherapy is still incomplete, TLRs on T cells are involved in the regulation of T cell function and serve as co-stimulatory molecules and activate T cell immunity. TLR agonists can activate T cell-mediated antitumor responses with both innate and adaptive immune responses to improve tumor therapy. Recently, novel drugs of TLR7 or TLR8 agonists with different scaffolds have been developed. These agonists lead to the induction of certain cytokines and chemokines that can be applied to the treatment of some diseases and can be used as good adjutants for vaccines. Furthermore, TLR7/8 agonists as potential therapeutics for tumor-targeted immunotherapy have been developed. In this review, we summarize the recent advances in the development of immunotherapy strategies targeting TLR7/8 in patients with various cancers and chronic hepatitis B.

PD-1 expression, among other immune checkpoints, on tumor-infiltrating NK and NKT cells is associated with longer disease-free survival in treatment-naïve CRC patients

A variety of variables, such as microsatellite instability or inflammatory mediators, are critical players in the development and progression of colorectal cancer (CRC). Natural killer (NK) and natural killer T (NKT) cells are involved in the prognoses of CRC. Immunological components of the tumor microenvironment (TME) impact cancer progression and therapeutic responses. We report that CRC patients with higher frequencies of tumor-infiltrating PD-1+ NK and NKT cells had significantly longer disease-free survival (DFS) than patients with lower frequencies. In agreement with that, patients with higher frequencies of tumor-infiltrating PD-1− NK and NKT cells showed shorter DFS. There were no significant associations between tumor-infiltrating PD-1+TIM-3+, PD-1+TIGIT+, PD-1+ICOS+, PD-1+LAG-3+ NK cells, and PD-1+TIM-3+, PD-1+TIGIT+, and PD-1+LAG-3+ NKT cells with DFS. This study highlights the significance of PD-1 expression on tumor-infiltrating NK and NKT cells and its association with disease prognoses in CRC patients.

Machine learning-based tumor-infiltrating immune cell-associated lncRNAs for predicting prognosis and immunotherapy response in patients with glioblastoma

Long noncoding ribonucleic acids (RNAs; lncRNAs) have been associated with cancer immunity regulation. However, the roles of immune cell-specific lncRNAs in glioblastoma (GBM) remain largely unknown. In this study, a novel computational framework was constructed to screen the tumor-infiltrating immune cell-associated lncRNAs (TIIClnc) for developing TIIClnc signature by integratively analyzing the transcriptome data of purified immune cells, GBM cell lines and bulk GBM tissues using six machine learning algorithms. As a result, TIIClnc signature could distinguish survival outcomes of GBM patients across four independent datasets, including the Xiangya in-house dataset, and more importantly, showed superior performance than 95 previously established signatures in gliomas. TIIClnc signature was revealed to be an indicator of the infiltration level of immune cells and predicted the response outcomes of immunotherapy. The positive correlation between TIIClnc signature and CD8, PD-1 and PD-L1 was verified in the Xiangya in-house dataset. As a newly demonstrated predictive biomarker, the TIIClnc signature enabled a more precise selection of the GBM population who would benefit from immunotherapy and should be validated and applied in the near future.

Metabolic profiles of regulatory T cells and their adaptations to the tumor microenvironment: implications for antitumor immunity

Characterized by the expression of the critical transcription factor forkhead box protein P3, regulatory T (Treg) cells are an essential part of the immune system, with a dual effect on the pathogenesis of autoimmune diseases and cancer. Targeting Tregs to reestablish the proinflammatory and immunogenic tumor microenvironment (TME) is an increasingly attractive strategy for cancer treatment and has been emphasized in recent years. However, attempts have been significantly hindered by the subsequent autoimmunity after Treg ablation owing to systemic loss of their suppressive capacity. Cellular metabolic reprogramming is acknowledged as a hallmark of cancer, and emerging evidence suggests that elucidating the underlying mechanisms of how intratumoral Tregs acquire metabolic fitness and superior immunosuppression in the TME may contribute to clinical benefits. In this review, we discuss the common and distinct metabolic profiles of Tregs in peripheral tissues and the TME, as well as the differences between Tregs and other conventional T cells in their metabolic preferences. By focusing on the critical roles of different metabolic programs, such as glycolysis, oxidative phosphorylation, fatty acid oxidation, fatty acid synthesis, and amino acid metabolism, as well as their essential regulators in modulating Treg proliferation, migration, and function, we hope to provide new insights into Treg cell-targeted antitumor immunotherapies.

Reshaping the systemic tumor immune environment (STIE) and tumor immune microenvironment (TIME) to enhance immunotherapy efficacy in solid tumors

The development of combination immunotherapy based on the mediation of regulatory mechanisms of the tumor immune microenvironment (TIME) is promising. However, a deep understanding of tumor immunology must involve the systemic tumor immune environment (STIE) which was merely illustrated previously. Here, we aim to review recent advances in single-cell transcriptomics and spatial transcriptomics for the studies of STIE, TIME, and their interactions, which may reveal heterogeneity in immunotherapy responses as well as the dynamic changes essential for the treatment effect. We review the evidence from preclinical and clinical studies related to TIME, STIE, and their significance on overall survival, through different immunomodulatory pathways, such as metabolic and neuro-immunological pathways. We also evaluate the significance of the STIE, TIME, and their interactions as well as changes after local radiotherapy and systemic immunotherapy or combined immunotherapy. We focus our review on the evidence of lung cancer, hepatocellular carcinoma, and nasopharyngeal carcinoma, aiming to reshape STIE and TIME to enhance immunotherapy efficacy.

Spatial Transcriptomics for Tumor Heterogeneity Analysis

The molecular heterogeneity of cancer is one of the major causes of drug resistance that leads to treatment failure. Thus, better understanding the heterogeneity of cancer will contribute to more precise diagnosis and improved patient outcomes. Although single-cell sequencing has become an important tool for investigating tumor heterogeneity recently, it lacks the spatial information of analyzed cells. In this regard, spatial transcriptomics holds great promise in deciphering the complex heterogeneity of cancer by providing localization-indexed gene expression information. This study reviews the applications of spatial transcriptomics in the study of tumor heterogeneity, discovery of novel spatial-dependent mechanisms, tumor immune microenvironment, and matrix microenvironment, as well as the pathological classification and prognosis of cancer. Finally, future challenges and opportunities for spatial transcriptomics technology’s applications in cancer are also discussed.

Novel insights into noncanonical open reading frames in cancer

With technological advances, previously neglected noncanonical open reading frames (nORFs) are drawing ever-increasing attention. However, the translation potential of numerous putative nORFs remains elusive, and the functions of noncanonical peptides have not been systemically summarized. Moreover, the relationship between noncanonical peptides and their counterpart protein or RNA products remains elusive and the clinical implementation of noncanonical peptides has not been explored. In this review, we highlight how recent technological advances such as ribosome profiling, bioinformatics approaches and CRISPR/Cas9 facilitate the research of noncanonical peptides. We delineate the features of each nORF category and the evolutionary process underneath the nORFs. Most importantly, we summarize the diversified functions of noncanonical peptides in cancer based on their subcellular location, which reflect their extensive participation in key pathways and essential cellular activities in cancer cells. Meanwhile, the equilibrium between noncanonical peptides and their corresponding transcripts or counterpart products may be dysregulated under pathological states, which is essential for their roles in cancer. Lastly, we explore their underestimated potential in clinical application as diagnostic biomarkers and treatment targets against cancer.

Pan-Cancer Analysis Identified CD93 as a Valuable Biomarker for Predicting Patient Prognosis and Immunotherapy Response

Background: The rapid development of immunotherapy has significantly improved patient outcomes in recent years. CD93, a novel biomarker expressed on vascular endothelial cells, is essential for tumor angiogenesis. Recent studies have shown that CD93 is closely related to immune cell infiltration and immunotherapy. However, its role in pan-cancer has not been reported.

Methods: The Cancer Genome Atlas (TCGA), Human Protein Atlas (HPA), cbioportal, Gene Expression Omnibus (GEO), Tumor Immune Estimation Resource (TIMER2.0), and the Tumor–Immune System Interactions and Drug Bank (TISIDB) databases were used to analyze CD93 in pan-cancers. R software was used for statistical analysis and mapping.

Results: There were significant differences in the expression of CD93 between tumor tissues and adjacent normal tissues in pan-cancer. The high expression of CD93 was associated with poor prognosis and high TNM stage in multiple tumor types. However, a high expression of CD93 was a protective factor in kidney renal clear cell carcinoma (KIRC). In addition, CD93 was closely related to immune cell infiltration in tumor tissues. Moreover, CD93 presented a robust correlation with immune modulators and immunotherapeutic markers [e.g., tumor mutation burden (TMB) and microsatellite instability (MSI)]. The results of gene set enrichment analysis (GSEA) showed that CD93 was correlated with tumor angiogenesis. Importantly, patients with a low expression of CD93 were more sensitive to immunotherapy in urothelial cancer.

Conclusion: CD93, which is involved in various immune responses, controls immune cell infiltration and impacts on the malignant properties of various cancer types. Therefore, CD93 has potential value to be biomarker for determining the prognosis and immune infiltration in multiple cancers.

Glioma targeted therapy: insight into future of molecular approaches

Gliomas are the common type of brain tumors originating from glial cells. Epidemiologically, gliomas occur among all ages, more often seen in adults, which males are more susceptible than females. According to the fifth edition of the WHO Classification of Tumors of the Central Nervous System (WHO CNS5), standard of care and prognosis of gliomas can be dramatically different. Generally, circumscribed gliomas are usually benign and recommended to early complete resection, with chemotherapy if necessary. Diffuse gliomas and other high-grade gliomas according to their molecule subtype are slightly intractable, with necessity of chemotherapy. However, for glioblastoma, feasible resection followed by radiotherapy plus temozolomide chemotherapy define the current standard of care. Here, we discuss novel feasible or potential targets for treatment of gliomas, especially IDH-wild type glioblastoma. Classic targets such as the p53 and retinoblastoma (RB) pathway and epidermal growth factor receptor (EGFR) gene alteration have met failure due to complex regulatory network. There is ever-increasing interest in immunotherapy (immune checkpoint molecule, tumor associated macrophage, dendritic cell vaccine, CAR-T), tumor microenvironment, and combination of several efficacious methods. With many targeted therapy options emerging, biomarkers guiding the prescription of a particular targeted therapy are also attractive. More pre-clinical and clinical trials are urgently needed to explore and evaluate the feasibility of targeted therapy with the corresponding biomarkers for effective personalized treatment options.