Prognostic Landscape of Tumor-Infiltrating T and B Cells in Human Cancer

Immunoscore Predicted by Dynamic Contrast-Enhanced Computed Tomography Can Be a Non-Invasive Biomarker for Immunotherapy Susceptibility of Hepatocellular Carcinoma

Background/Objectives: Although immunotherapy is the primary treatment option for intermediate-stage hepatocellular carcinoma (HCC), its efficacy varies. This study aimed to identify non-invasive imaging biomarkers predictive of the immunoscore linked to dynamic contrast-enhanced computed tomography (CECT). Methods: We performed immunohistochemical staining with CD3+ and CD8+ antibodies and counted the positive cells in the invasive margin (IM) and central tumor (CT), converting them to an immunoscore of 0 to 4 points. We assessed the dynamic CECT findings obtained from 96 patients who underwent hepatectomy for HCC and evaluated the relationship between dynamic CECT findings and immunoscores. For validation, we assessed the treatment effects on 81 nodules using the Response Evaluation Criteria in Solid Tumors in another cohort of 41 patients who received combined immunotherapy with atezolizumab and bevacizumab (n = 27) and durvalumab and tremelizumab (n = 14). Results: HCCs with peritumoral enhancement in the arterial phase (p < 0.001) and rim APHE (p = 0.009) were associated with the immunoscore in univariate linear regression analysis and peritumoral enhancement in the arterial phase (p = 0.004) in multivariate linear regression analysis. The time to nodular progression in HCCs with peritumoral enhancement in the arterial phase was significantly longer than that in HCCs without this feature (p < 0.001). Conclusions: We identified HCCs with peritumoral enhancement in the arterial phase as a noninvasive imaging biomarker to predict immune-inflamed HCC with a high immunoscore tendency. These HCCs were most likely to respond to combined immunotherapy.

Combining a deep learning model with clinical data better predicts hepatocellular carcinoma behavior following surgery

Hepatocellular carcinoma (HCC) is among the most common cancers worldwide, and tumor recurrence following liver resection or transplantation is one of the highest contributors to mortality in HCC patients after surgery. Using artificial intelligence (AI), we developed an interdisciplinary model to predict HCC recurrence and patient survival following surgery. We collected whole-slide H&E images, clinical variables, and follow-up data from 300 patients with HCC who underwent transplant and 169 patients who underwent resection at the Cleveland Clinic. A deep learning model was trained to predict recurrence-free survival (RFS) and disease-specific survival (DSS) from the H&E-stained slides. Repeated cross-validation splits were used to compute robust C-index estimates, and the results were compared to those obtained by fitting a Cox proportional hazard model using only clinical variables. While the deep learning model alone was predictive of recurrence and survival among patients in both cohorts, integrating the clinical and histologic models significantly increased the C-index in each cohort. In every subgroup analyzed, we found that a combined clinical and deep learning model better predicted post-surgical outcome in HCC patients compared to either approach independently.

NSG2: a promising prognostic marker shaping the immune landscape of breast cancer

Background

Breast cancer (BC) remains a significant health issue globally and most common cause of mortality in women. Enhancing our understanding on biomarkers may greatly improve both diagnostic and therapeutic approaches to this disease.

Methods

We retrospectively assessed tumor samples from 228 BC cases and 51 normal samples, alongside relevant clinical data. Neuronal vesicle trafficking associated 2(NSG2) expression was evaluated through bioinformatics and multiplex immunohistochemistry. Associations between NSG2 expression, tumor-infiltrating immune cells (TIICs), immune checkpoints, and clinical outcomes were investigated.

Results

NSG2 was present in both breast cancer cells and adjacent stromal cells. Increased NSG2 expression in cancer cells correlated with greater tumor size, distant metastasis, and more advanced clinical stages. Kaplan-Meier survival and multivariate analyses identified NSG2 expression in both cancer and stromal cells as an independent prognostic factor for breast cancer survival. Elevated NSG2 levels both in cancer and stroma cells were linked to increased CD4+ T, CD8+ T, and Lamp3+ dendritic cells infiltration in stromal regions (P < 0.05). Conversely, the expression of NSG2 in the stroma was negatively correlated with CD20+ B cells (P < 0.05). Additionally, NSG2 expression was found to be associated with CTLA-4 levels (P < 0.05).

Conclusion

NSG2 seems to be a significant component of the BC immune microenvironment and may serve as an important prognostic marker.

Potentially functional variants of INPP5D and EXOSC3 in immunity B cell-related genes are associated with non-small cell lung cancer survival

B cells are adaptive immune cells in the tumor microenvironment and play an important role in tumor development and metastasis. However, the roles of genetic variants of the immunity B cell-related genes in the survival of patients with non-small cell lung cancer (NSCLC) remain unknown. In the present study, we first evaluated associations between 10,776 single nucleotide polymorphisms (SNPs) in 220 immunity B cell-related genes and survival of NSCLC in a discovery dataset of 1,185 patients from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. We found that 369 SNPs were significantly associated with overall survival (OS) of NSCLC in multivariable Cox proportional hazards regression analysis (P ≤ 0.05, Bayesian false discovery probability ≤ 0.80), of which 18 SNPs were validated in another independent genotyping dataset of 984 patients from the Harvard Lung Cancer Susceptibility (HLCS) Study. We then performed linkage disequilibrium (LD) analysis, followed by stepwise analysis with a multivariable Cox regression model. Finally, two independent SNPs, inositol polyphosphate-5-phosphatase D (INPP5D) rs13385922 C>T and exosome component 3 (EXOSC3) rs3208406 A>G, remained significantly associated withNSCLC OS with a combined hazards ratio (HR) of 1.14 (95% confidence interval = 1.06-1.23, P = 2.41×10-4) and 1.20 (95% confidence interval = 1.14-1.28, P = 3.41×10-9), respectively. Furthermore, NSCLC patients with the combination of unfavorable genotypes for these two SNPs were associated with a poor OS (P trend = 0.0002) and disease-specific survival (DSS, P trend < 0.0001) in the PLCO dataset. Expression quantitative trait loci (eQTL) analysis suggested that the INPP5D rs6782875 T allele was significantly correlated with elevated INPP5D mRNA expression levels in normal lung tissues and whole blood samples, while the EXOSC3 rs3208406 G allele was significantly correlated with increased EXOSC3 mRNA expression levels in normal lung tissues. Our data indicated that genetic variants in these immunity B cell-related genes may predict NSCLC survival possibly by influencing the gene expression.

Prognostic significance of peripheral and tumor-infiltrating lymphocytes in newly diagnosed stage III/IV non-small-cell lung cancer

BACKGROUND AND AIM

Lymphocytes are effector cells that fight cancer by killing tumor cells. Here, we aim to explore the prognostic significance of both peripheral and tumor-infiltrating lymphocytes (TILs) in newly diagnosed stage III/IV non-small-cell lung cancer (NSCLC).

MATERIALS AND METHODS

In total, 105 cases of newly diagnosed stage III/IV NSCLC from July 2017 to October 2022 at the Tianjin Beichen Hospital were retrospectively investigated. Peripheral blood samples at the time of diagnosis and tumor tissue slices from these patients were collected. General peripheral blood cell composition and TILs were measured and analyzed via an automatic blood analyzer and immunofluorescence staining analysis. The overall survival (OS) time of all patients was also obtained and analyzed.

RESULTS

The median overall survival (mOS) of all patients is 12 months. The 1-, 2-, and 3-year overall survival rates were 60.5, 28.4, and 18.6%, respectively. Peripheral lymphocyte and neutrophil percentages, serum C-reactive protein (CRP) expression, tumor size, and tumor pathology are the prognostic factors of OS for newly diagnosed stage III/IV NSCLC patients. Moreover, patients with high tumor CD4+ and CD8+ T cell infiltration survived significantly longer compared to patients with low tumor CD4+ and CD8+ T cell infiltration (p < 0.0001 and p = 0.011, respectively). Compared to low tumor CD33+ cell infiltration, high tumor CD33+ cell infiltration was associated with worse OS (p = 0.018). High tumor CD8+ T cell infiltration was associated with lower peripheral lymphocyte number, lower serum CRP expression, smaller tumor size, and better tumor pathology (p = 0.012, p = 0.040, p = 0.012, and p = 0.029, respectively).

CONCLUSION

Increased numbers of peripheral lymphocytes, CD33+ cells, CD4+ TILs, and CD8+ TILs were significantly associated with OS in newly diagnosed stage III/IV NSCLC patients, which were positively associated with several basic clinical factors.

Patterns of B-cell lymphocyte expression changes in pre- and post-malignant prostate tissue are associated with prostate cancer progression

BACKROUND

Inflammation characterized by the presence of T and B cells is often observed in prostate cancer, but it is unclear how T- and B-cell levels change during carcinogenesis and whether such changes influence disease progression.

METHODS

The study used a retrospective sample of 73 prostate cancer cases (45 whites and 28 African Americans) that underwent surgery as their primary treatment and had a benign prostate biopsy at least 1 year before diagnosis. CD3+, CD4+, and CD20+ lymphocytes were quantified by immunohistochemistry in paired pre- and post-diagnostic benign prostate biopsy and tumor surgical specimens, respectively. Clusters of similar trends of expression across two different timepoints and three distinct prostate regions-benign biopsy glands (BBG), tumor-adjacent benign glands (TAG), and malignant tumor glandular (MTG) regions-were identified using Time-series Anytime Density Peaks Clustering (TADPole). A Cox proportional hazards model was used to estimate the hazard ratio (HR) of time to biochemical recurrence associated with region-specific lymphocyte counts and regional trends.

RESULTS

The risk of biochemical recurrence was significantly reduced in men with an elevated CD20+ count in TAG (HR = 0.81, p = 0.01) after adjusting for covariates. Four distinct patterns of expression change across the BBG-TAG-MTG regions were identified for each marker. For CD20+, men with low expression in BBG and higher expression in TAG compared to MTG had an adjusted HR of 3.06 (p = 0.03) compared to the reference group that had nominal differences in CD20+ expression across all three regions. The two CD3+ expression patterns that featured lower CD3+ expression in the BBG compared to the TAG and MTG regions had elevated HRs ranging from 3.03 to 4.82 but did not reach statistical significance.

CONCLUSIONS

Longitudinal and spatial expression patterns of both CD3+ and CD20+ suggest that increased expression in benign glands during prostate carcinogenesis is associated with an aggressive disease course.

Immune gene signatures as prognostic criteria for cancer patients

Recently, the possibility of using immune gene signatures (IGSs) has been considered as a novel prognostic tool for numerous cancer types. State-of-the-art methods of genomic, transcriptomic, and protein analysis have allowed the identification of a number of immune signatures correlated to disease outcome. The major adaptive and innate immune components are the T lymphocytes and macrophages, respectively. Herein, we collected essential data on IGSs consisting of subsets of T cells and tumor-associated macrophages and indicating cancer patient outcomes. We discuss factors that can introduce errors in the recognition of immune cell types and explain why the significance of immune signatures can be interpreted with uncertainty. The unidirectional functions of cell types should be entirely addressed in the signatures constructed by the combination of innate and adaptive immune cells. The state of the antitumor immune response is the key basis for IGSs and should be considered in gene signature construction. We also analyzed immune signatures for the prediction of immunotherapy response. Finally, we attempted to explain the present-day limitations in the use of immune signatures as robust criteria for prognosis.

Predictive biomarkers of colon cancer immunotherapy: Present and future

Immunotherapy has revolutionized colon cancer treatment. Immune checkpoint inhibitors (ICIs) have shown clinical benefits for colon cancer patients, especially those with high microsatellite instability (MSI-H). In 2020, the US Food and Drug Administration (FDA)-approved ICI pembrolizumab as the first-line treatment for metastatic MSI-H colon cancer patients. Additionally, neoadjuvant immunotherapy has presented efficacy in treating early-stage colon cancer patients. Although MSI has been thought of as an effective predictive biomarker for colon cancer immunotherapy, only a small proportion of colon cancer patients were MSI-H, and certain colon cancer patients with MSI-H presented intrinsic or acquired resistance to immunotherapy. Thus, further search for predictive biomarkers to stratify patients is meaningful in colon cancer immunotherapy. Except for MSI, other biomarkers, such as PD-L1 expression level, tumor mutation burden (TMB), tumor-infiltrating lymphocytes (TILs), certain gut microbiota, ctDNA, and circulating immune cells were also proposed to be correlated with patient survival and ICI efficacy in some colon cancer clinical studies. Moreover, developing new diagnostic techniques helps identify accurate predictive biomarkers for colon cancer immunotherapy. In this review, we outline the reported predictive biomarkers in colon cancer immunotherapy and further discuss the prospects of technological changes for biomarker development in colon cancer immunotherapy.

Serum BRD2 autoantibody in hepatocellular carcinoma and its detection using mimotope peptide‑conjugated BSA

Tumor‑associated (TA) autoantibodies are considered to be promising biomarkers for the early detection of cancer, prior to the development of clinical symptoms. In the present study, a novel TA autoantibody was detected, which may prove to be useful as a diagnostic marker of human HCC using an HBx‑transgenic (HBx‑tg) hepatocellular carcinoma (HCC) mouse model. Its target antigen was identified as the bromodomain‑containing protein 2 (BRD2), a transcriptional regulator that plays a pivotal role in the transcriptional control of diverse genes. BRD2 was upregulated in HCC tissues of the H‑ras12V‑tg mouse and human subjects, as demonstrated using western blotting or immunohistochemical analysis, with the BRD2 autoantibody. In addition, the truncated BRD2 reactive to the BRD2 autoantibody was detected in tumor cell‑derived exosomes, which possibly activated TA immune responses and the generation of autoantibodies. For the detection of the serum BRD2 autoantibody, epitope mimicries of autoantigenic BRD2 were screened from a random cyclic peptide CX₇C library with the BRD2 autoantibody. A mimotope with the sequence of CTSVFLPHC, which was cyclized by one pair of cysteine residues, exhibited high affinity to the BRD2 autoantibody and competitively inhibited the binding of the autoantibody to the cellular BRD2 antigen. The use of this cyclic peptide as a capture antigen in human serum enzyme‑linked immunosorbent assay allowed the distinction of patients with HCC from healthy subjects with 64.41% sensitivity and 82.42% specificity (area under the ROC curve, 0.7761), which is superior to serum alpha‑fetoprotein (AFP; 35.83% sensitivity; 100% specificity; area under the ROC curve, 0.5337) for the diagnosis of HCC. In addition, the detection of the BRD2 autoantibody combined with other autoantibody biomarkers or AFP has increased the accuracy of HCC diagnosis, suggesting that the combinational detection of cancer biomarkers, including the BRD2 autoantibody, is a promising assay for HCC diagnosis.

Deciphering diffuse glioma immune microenvironment as a key to improving immunotherapy results

PURPOSE OF REVIEW

Immunotherapeutic approaches have yet to demonstrate their clinical efficacy in diffuse gliomas. Evidence is mounting that the central nervous system is subject to immune surveillance, but brain tumours manage to escape due to factors intrinsic to their tumoral immune microenvironment (TME). This review aims to discuss the recently characterized molecular bases of the glioma TME and the potentially actionable targets to improve immunotherapeutic results in these hard-to-treat cancers.

RECENT FINDINGS

Single-cell studies defined the composition of the glioma immune TME and its peculiarities compared with other solid cancers. In isocitrate dehydrogenase (IDH) wildtype gliomas, the TME is enriched in myeloid cells (monocyte-derived macrophages and resident microglia) with mainly immunosuppressive functions. Lymphocytes can infiltrate the glioma TME, but are exposed to multiple immunomodulating signals that render them in a state of deep exhaustion. IDH mutant gliomas produce the oncometabolite D-2-hydroxyglutarate with negative effects on leukocyte recruitment and function, resulting in the induction of an 'immune-desert' TME.

SUMMARY

Several molecular pathways have been recently identified in the induction of an 'immune-hostile' microenvironment in diffuse gliomas, unravelling potential vulnerabilities to targeted immunotherapies.

Comprehensive Analysis of Role of Cyclin-Dependent Kinases Family Members in Colorectal Cancer

Background

Cyclin-dependent kinases (CDKs) are cell cycle regulators, and abnormal activation can accelerate tumor cell proliferation. However, The relation between CDKs dysregulation to colorectal cancer incidence and progression have not been examined in detail. Methods:Differences in CDKs expression between colorectal cancer and normal tissues, associations between expression and clinical prognosis, incidence and frequencies of CDKs gene mutations, and the influences of CDKs on tumor infiltration by immune cells were examined by analyses of Oncomine, Gene Expression Profiling Interactive Analysis, Kaplan-Meier plotter, cBioPortal, GeneMANIA, and TIMER databases.

Results

Colorectal cancer tissues showed enhanced expression levels of CDKs 1/2/4/5/6/8/12/13/19 but reduced CDK3 expression. CDK7 was highly expressed in some colorectal cancer tissues but downregulated in others. Expression levels of CDK1/3/4/7/8/10/11b/13/18/19/20 were correlated with clinical stage, and CDK 5/10/12/16 expression levels predicted prognosis and survival. Differential CDKs expression correlated with cell cycle progression, amino acid polypeptide modifications, and activation of other protein kinases. Expression levels of all CDKs except CDK16 were correlated with infiltration of CD4+T, CD8+T, B and Tregs cells.

Conclusions

CDK 1 and 4 could be used as diagnostic biomarkers for CRC. CDK 5/10/12/16 can be utilized as prognostic biomarkers.