A Comprehensive Immunologic Portrait of Triple-Negative Breast Cancer

Injectable supramolecular hydrogel co-loading abemaciclib/NLG919 for neoadjuvant immunotherapy of triple-negative breast cancer

The efficacy of cancer immunotherapy relies on a sufficient amount of functional immune cells. Triple-negative breast cancer lacks enough immune cell infiltration, and adjuvant therapy is necessary to prime anti-tumor immunity. However, the improvement in efficacy is unsatisfactory with concern about inducing systemic immunotoxicity. Herein, we create an abemaciclib-loaded supramolecular peptide hydrogel formed by peptide-drug amphiphiles for neoadjuvant immunotherapy of triple-negative breast cancer, where the amphiphile is a conjugate of a β-sheet-forming peptide with 1-cyclohexyl-2-(5H-imidazo[5,1-a]isoindol-5-yl)ethanol (NLG919), an inhibitor of indoleamine 2,3-dioxygenase 1. The hydrogel can be injected into the tumor site and retained for at least one week for the sustained release of both abemaciclib and NLG919. The abemaciclib is able to induce immunogenic cell death of cancer cells and increase interleukin-2 secretion by cytotoxic T lymphocytes. Abemaciclib adversely upregulates indoleamine 2,3-dioxygenase 1, whose kynurenine production activity is inhibited by NLG919. The neoadjuvant immunotherapy reduces tumor recurrence and pulmonary metastasis and prolongs the survival of animals. This hydrogel provides a potential platform for neoadjuvant immunotherapy of triple-negative breast cancer with reduced toxicity compared with free abemaciclib.

Exploring the role of ELOVLs family in lung adenocarcinoma based on bioinformatic analysis and experimental validation

BACKGROUND

The role of lipid metabolic reprogramming in the development of various types of cancer has already been established. However, the exact biological function and significance of the elongation of very-long-chain fatty acids (ELOVLs) gene family, which can affect fatty acid metabolism, is still not well understood in lung adenocarcinoma (LUAD). The aim of our study is to explore whether there are genes related to the pathogenesis of LUAD in the ELOVLs family, and even to guide clinical medication and potential prognostic indicators.

METHODS

Gene expression profiling interactive analysis (GEPIA), human protein atlas (HPA), cBioPortal, Kaplan-Meier (KM) plotter, single-sample Gene Set Enrichment Analysis (ssGSEA) algorithm and SubMap algorithms were utilized to analyze the role of ELOVLs in the LUAD. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analysis, cell counting kit-8 (CCK8), colony formation, wound healing, transwell migration assays and fatty acid metabolism detection were employed to confirm the significant role of ELOVL6 in vitro experiment.

RESULTS

Our results revealed that mRNA expression levels of ELOVL2, ELOVL4 and ELOVL6 and protein expression levels of ELOVL5 and ELOVL6 were elevated in LUAD tissues compared to normal subjects. The low-expressing ELOVL6 group showed superior overall survival (OS) and disease-specific survival (DSS) versus the high-expressing group. Meanwhile, patients with low-ELOVL6 expression were more sensitive to the 4 representative chemotherapeutic agents. In vitro, we revealed that interfering with ELOVL6 could influence the viability, proliferation, migration capacity and fatty acid metabolism of LUAD cells (A549 and H1299).

CONCLUSIONS

Our study indicated that ELOVL6 could be used as an indicator to evaluate the prognosis and therapeutic effect, and even potential therapeutic target for patients with LUAD.

Correlation analysis of DLG5 and PD-L1 expression in triple-negative breast cancer

BACKGROUND

Triple-negative breast cancer (TNBC) is among the most aggressive forms of breast cancer, characterized by a dismal prognosis. In the absence of drug-targetable receptors, chemotherapy remains the sole systemic treatment alternative. Recent advancements in immunotherapy, particularly immune checkpoint inhibitors (ICIs) that target programmed death 1/programmed death ligand 1 (PD-1/PD-L1) and cytotoxic T lymphocyte associated antigen 4 (CTLA-4), have provided renewed optimism for the treatment of patients with TNBC. Prior research has indicated that the expression level of the cell polarity protein discs large homolog 5 (DLG5) correlates with the malignant progression and prognosis of breast cancer; nevertheless, its influence on PD-L1 expression and its function in immunotherapy for TNBC require further investigation.

METHODS

The hypoxia cell model was established by simulating the cell hypoxic microenvironment in the human SUM159 and MDA-MB-231 cell lines using cobalt II chloride (CoCl2). A combination of PD-L1 inhibitors and DLG5 RNA interference techniques was used, along with various methods including cell counting kit-8 (CCK-8), colony formation, wound healing, transwell migration, reverse transcription-quantitative real-time PCR (RT-qPCR), immunofluorescence, immunohistochemical staining (IHC), expression analysis from datasets and western blotting. These methods were employed to evaluate changes in cell proliferation, migration, and the expression levels of PD-L1 and DLG5. Additionally, the correlation between the expression of PD-L1 and DLG5 in clinical samples was analyzed.

RESULTS

(1) In vitro experiments, a cellular hypoxia model was effectively established utilizing 150 µM CoCl₂. Under these conditions, cell clone formation, invasiveness, and migration rate were all significantly inhibited. (2) The expression levels of DLG5 and PD-L1 were significantly increased in both MDA-MB-231 and SUM159 cells following treatment with 150 µM CoCl₂. (3) Silencing DLG5 resulted in a considerable upregulation of PD-L1 expression in MDA-MB-231 and SUM159 cells under normoxic circumstances, but it was markedly downregulated under hypoxic settings. Inhibition of PD-L1 expression resulted in a considerable increase in DLG5 expression under normoxic conditions, but it decreased under hypoxic conditions. Correlation research demonstrated an inverse association between the expression of DLG5 and PD-L1 in TNBC tissues.

CONCLUSION

This study provides new theoretical evidence and potential therapeutic targets for the immunotherapy strategies of TNBC, holding significant clinical application value.

Real‑world evaluation of the efficacy of immune checkpoint inhibitors in the treatment of metastatic breast cancer

The present study aimed to assess the efficacy and safety of immune checkpoint inhibitor (ICI)-based therapy in patients with metastatic breast cancer (MBC). Therefore, eligible patients with histologically confirmed MBC, treated with ICI-based therapy, were enrolled. The primary endpoint was progression-free survival (PFS) and the secondary endpoints included objective response rate (ORR), disease control rate (DCR), overall survival (OS) and safety. A total of 90 patients with MBC, treated with ICI-based therapy, with different treatment lines, were included in the present study. The median age was 50 years (range, 27-76). The predominant tumor subtypes were triple negative (53.3%) and luminal (31.1%) breast cancer. The majority of patients (61.1%) were heavily pretreated (lines of treatment, ≥3). Approximately half of the patients (46.7%) had ≥3 metastatic sites. The overall ORR was 36.7% (33/90 patients), while a DCR of 78.9% (71/90 patients) was also recorded. With a median follow-up of 16.0 months, the median PFS and OS were 4.9 months [95% confidence interval (CI), 3.8-6.1] and 13.9 months (95% CI, 9.5-18.2), respectively. Patients treated with ICIs as first-line therapy exhibited notable improvement, with a median PFS of 11.0 months (95% CI, 6.0-16.0) and a median OS of 24.3 months (95% CI, 11.4-37.2). In addition, the pretreatment blood platelet-to-lymphocyte ratio was an independent risk factor for PFS [hazard ratio (HR)=2.406; 95% CI, 1.325-4.370; P=0.004] and OS (HR=2.376; 95% CI, 1.059-5.328; P=0.036). The most common adverse events were nausea (44.4%), neutropenia (42.0%) and alanine aminotransferase/aspartate aminotransferase elevation (22.2%). Furthermore, three (3.3%) patients developed grade 1/2 immuno-related toxicity and recovered after supportive care. Overall, the present study suggested that the ICI-based therapy exhibited encouraging clinical outcomes with manageable toxicity in patients with MBC in real-world settings, with the most favorable efficacy in first-line treatment.

Cryoablation of primary breast cancer tumors induces a systemic abscopal effect altering TIME (Tumor Immune Microenvironment) in distant tumors

Introduction

Despite recent advances, triple-negative breast cancer (TNBC) patients remain at high risk for recurrence and metastasis, which creates the need for innovative therapeutic approaches to improve patient outcomes. Cryoablation is a promising, less invasive alternative to surgical resection, capable of inducing tumor necrosis via freeze/thaw cycles. Necrotic cell death results in increased inflammatory signals and release of preserved tumor antigens, which have the potential to boost the local and systemic anti-tumor immune response. Thus, compared to surgery, cryoablation enhances the activation of T cells leading to an improved abscopal effect, defined as the occurrence of a systemic response after local treatment. We previously showed with a bilateral-tumor mouse model of TNBC that cryoablation of the primary tumor leads to increased infiltration of distant (abscopal) tumors by tumor infiltrating lymphocytes (TILs) and decreased rates of recurrence and metastasis. However, the early drivers of the cryoablation generated abscopal effect are still unknown and knowledge of the mechanism could provide insight into improving the anti-tumor immune response through pharmacologic immune modulation in addition to cryoablation.

Methods

One million 4T1-12B-luciferase expressing cells were transplanted into the mammary fat pad of BALB/c mice. Two weeks later, left (primary) tumors were either resected or cryoablated. A week after the procedure, right (abscopal) and left tumors, along with spleen, tumor-draining lymph node and blood were collected and processed for flow cytometry and/or RNA-sequencing and immunofluorescence.

Results

Here we show that cryoablation of mouse mammary carcinomas results in smaller abscopal tumors that harbor increased frequencies of anti-tumor cells [such as natural killer (NK) cells], accompanied by a systemic increase in the frequency of migratory conventional type 1 dendritic cells (cDC1; CD103+ XCR1+), compared to resection. The changes in cell frequencies are mirrored by the immune gene signature of the abscopal tumors, with cryoablation inducing genes involved with NK cell activation and leukocyte-mediated toxicity, including IL11ra1 and Pfr1.

Conclusions

These results better define the early mechanisms through which cryoablation improves tumor elimination, which is mediated by enhanced frequencies of anti-tumoral cells such as NK and cDC1s at the abscopal tumor and in the spleen of mice treated with cryoablation, respectively.

The association of HIV status with triple-negative breast cancer in patients with breast cancer in South Africa: a cross-sectional analysis of case-only data from a prospective cohort study

BACKGROUND

Breast cancer is the most common malignancy diagnosed among women in South Africa, with the aggressive triple-negative subtype comprising approximately 15% of breast cancers in this population. South Africa has the largest population of people with HIV in the world. This study aims to evaluate the association between HIV status and the proportion of patients with breast cancer with the triple-negative subtype.

METHODS

We did a cross-sectional analysis of case-only data from the South African Breast Cancer and HIV Outcomes (SABCHO) study, a prospective cohort study recruiting patients with newly diagnosed breast cancer at six public hospitals in South Africa. We analysed data from patients who enrolled in SABCHO between Jan 1, 2015, and Jan 18, 2022. Women aged 18 years or older with newly diagnosed and histologically confirmed invasive breast cancer were eligible. Participants were classified as HIV-positive or HIV-negative by use of an ELISA-based HIV test done at the time of enrolment. We developed multivariable logistic regression models to test for an association between HIV status and the proportion of triple-negative relative to non-triple-negative breast cancers while adjusting for demographic and reproductive risk factors.

FINDINGS

Of the 4122 patients enrolled in the SABCHO cohort within our study timeframe, 239 patients were excluded due to unknown breast cancer subtype (n=141), HIV status (n=97), or race (n=1). 3883 women with breast cancer were included in the study, of whom 637 (16·4%) had triple-negative breast cancer, 894 (23·0%) were HIV-positive, and 186 (4·8%) had triple-negative breast cancer and HIV. Triple-negative breast cancer accounted for 186 (20·8%) of 894 breast cancers among women who were HIV-positive and 451 (15·1%) of 2989 breast cancers among women who were HIV-negative (p<0·0001). In the fully adjusted logistic regression model, HIV-positive status was associated with an increased proportion of triple-negative breast cancer (adjusted odds ratio [OR] 1·39, 95% CI 1·12-1·74, compared with women who were HIV-negative). When compared with women who were HIV-negative, the association between HIV-positive status and the proportion of triple-negative breast cancer was strongest among the subgroup of women with a duration of HIV infection of 2 years or longer (1·57, 1·23-2·00) and those on antiretroviral therapy (ART; 1·47, 1·16-1·87).

INTERPRETATION

Patients with breast cancer and chronic HIV who are on ART are more likely to have triple-negative breast cancer than patients with breast cancer without HIV. This association is independent of age, race, and reproductive factors.

FUNDING

US National Institutes of Health, University of the Witwatersrand, South Africa Medical Research Council Common Epithelial Cancers Research Center, Conquer Cancer Foundation, and Varmus Global Scholars Fund.

Inflammatory response signature score model for predicting immunotherapy response and pan-cancer prognosis

Background

Inflammatory responses influence the outcome of immunotherapy and tumorigenesis by modulating host immunity. However, systematic inflammatory response assessment models for predicting cancer immunotherapy (CIT) responses and survival across human cancers remain unexplored. Here, we investigated an inflammatory response score model to predict CIT responses and patient survival in a pan-cancer analysis.

Methods

We retrieved 12 CIT response gene expression datasets from the Gene Expression Omnibus database (GSE78220, GSE19423, GSE100797, GSE126044, GSE35640, GSE67501, GSE115821 and GSE168204), Tumor Immune Dysfunction and Exclusion database (PRJEB23709, PRJEB25780 and phs000452.v2.p1), European Genome-phenome Archive database (EGAD00001005738), and IMvigor210 cohort. The tumor samples from six cancers types: metastatic urothelial cancer, metastatic melanoma, gastric cancer, primary bladder cancer, renal cell carcinoma, and non-small cell lung cancer.We further established a binary classification model to predict CIT responses using the least absolute shrinkage and selection operator (LASSO) computational algorithm.

Findings

The model had high predictive accuracy in both the training and validation cohorts. During sub-group analysis, area under the curve (AUC) values of 0.82, 0.80, 0.71, 0.7, 0.67, and 0.64 were obtained for the non-small cell lung cancer, gastric cancer, metastatic urothelial cancer, primary bladder cancer, metastatic melanoma, and renal cell carcinoma cohorts, respectively. CIT response rates were higher in the high-scoring training cohort subjects (51%) than the low-scoring subjects (27%). The five-year survival rates in the high- and low score groups of the training cohorts were 62% and 21%, respectively, while those of the validation cohorts were 54% and 22%, respectively (P < 0·001 in all cases). Inflammatory response signature score derived from on-treatment tumor specimens are highly predictive of response to CIT in patients with metastatic melanoma. A significant correlation was observed between the inflammatory response scores and tumor purity. Regardless of the tumor purity, patients in the low score group had a significantly poorer prognosis than those in the high score group. Immune cell infiltration analysis indicated that in the high score cohort, tumor-infiltrating lymphocytes were significantly enriched, particularly effector and natural killer cells. Inflammatory response scores were positively correlated with immune checkpoint genes, suggesting that immune checkpoint inhibitors may have benefited patients with high scores. Analysis of signature scores across different cancer types from The Cancer Genome Atlas revealed that the prognostic performance of inflammatory response scores for survival in patients who have not undergone immunotherapy can be affected by tumor purity. Interleukin 21 (IL21) had the highest weight in the inflammatory response model, suggesting its vital role in the prediction mode. Since the number of metastatic melanoma patients (n = 429) was relatively large among CIT cohorts, we further performed a co-culture experiment using a melanoma cell line and CD8 + T cell populations generated from peripheral blood monocytes. The results showed that IL21 therapy combined with anti-PD1 (programmed cell death 1) antibodies (trepril monoclonal antibodies) significantly enhanced the cytotoxic activity of CD8 + T cells against the melanoma cell line.

Conclusion

In this study, we developed an inflammatory response gene signature model that predicts patient survival and immunotherapy response in multiple malignancies. We further found that the predictive performance in the non-small cell lung cancer and gastric cancer group had the highest value among the six different malignancy subgroups. When compared with existing signatures, the inflammatory response gene signature scores for on-treatment samples were more robust predictors of the response to CIT in metastatic melanoma.

Thematic trends and knowledge-map of tumor-infiltrating lymphocytes in breast cancer: a scientometric analysis

Background

Tumor-infiltrating lymphocytes (TILs), essential for the anti-tumor response, are now recognized as promising and cost-effective biomarkers with both prognostic and predictive value. They are crucial in the precision treatment of breast cancer, particularly for predicting clinical outcomes and identifying candidates for immunotherapy. This study aims to encapsulate the current knowledge of TILs in breast cancer research while evaluating research trends both qualitatively and quantitatively.

Methods

Publications on TILs in breast cancer studies from January 1, 2004, to December 31, 2023, were extracted from the Web of Science Core Collection. Co-occurrence and collaboration analyses among countries/regions, institutions, authors, and keywords were performed with Bibliometrix R packages and VOSviewer software. CiteSpace was used for reference and keyword burst detection, while high-frequency keyword layouts were generated using BICOMB. gCLUTO was employed for biclustering analysis of the binary co-keyword matrix.

Results

A total of 2,066 articles on TILs in breast cancer were identified. Between 2004 and 2023, the USA and Milan University led productivity in terms of country/region and institution, respectively. The journals "CANCERS," "Breast Cancer Research and Treatment," and "Frontiers in Oncology" published the most articles on this topic. Loi S was the leading author, with the highest number of publications and co-citations. Co-keyword analysis revealed six research hotspots related to TILs in breast cancer. The pathological assessment of TILs using artificial intelligence (AI) remains in its early stages but is a key focus. Burst detection of keywords indicated significant activity in "immune cell infiltration", "immune checkpoint inhibitors", and "hormone receptor" over the past three years.

Conclusion

This study reviews recent advancements and trends in TILs research in breast cancer using scientometric analysis. The findings offer valuable insights for funding decisions and developing innovative strategies in TILs research, highlighting current research frontiers and trends.

mtPCDI: a machine learning-based prognostic model for prostate cancer recurrence

Background

This research seeks to formulate a prognostic model for forecasting prostate cancer recurrence by examining the interaction between mitochondrial function and programmed cell death (PCD).

Methods

The research involved analyzing four gene expression datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) using univariate Cox regression. These analyses identified genes linked with mitochondrial function and PCD that correlate with recurrence prognosis. Various machine learning algorithms were then employed to construct an optimal predictive model.

Results

A key outcome was the creation of a mitochondrial-related programmed cell death index (mtPCDI), which effectively predicts the prognosis of prostate cancer patients. It was observed that individuals with lower mtPCDI exhibited higher immune activity, correlating with better recurrence outcomes.

Conclusion

The study demonstrates that mtPCDI can be used for personalized risk assessment and therapeutic decision-making, highlighting its clinical significance and providing insights into the biological processes affecting prostate cancer recurrence.

Identifying Diffuse Glioma Subtypes Based on Pathway Enrichment Evaluation

Gliomas are highly heterogeneous in molecular, histology, and microenvironment. However, a classification of gliomas by integrating different tumor microenvironment (TME) components remains unexplored. Based on the enrichment scores of 17 pathways involved in immune, stromal, DNA repair, and nervous system signatures in diffuse gliomas, we performed consensus clustering to uncover novel subtypes of gliomas. Consistently in three glioma datasets (TCGA-glioma, CGGA325, and CGGA301), we identified three subtypes: Stromal-enriched (Str-G), Nerve-enriched (Ner-G), and mixed (Mix-G). Ner-G was charactered by low immune infiltration levels, stromal contents, tumor mutation burden, copy number alterations, DNA repair activity, cell proliferation, epithelial-mesenchymal transformation, stemness, intratumor heterogeneity, androgen receptor expression and EGFR, PTEN, NF1 and MUC16 mutation rates, while high enrichment of neurons and nervous system pathways, and high tumor purity, estrogen receptor expression, IDH1 and CIC mutation rates, temozolomide response rate and overall and disease-free survival rates. In contrast, Str-G displayed contrastive characteristics to Ner-G. Our analysis indicates that the heterogeneity between glioma cells and neurons is lower than that between glioma cells and immune and stromal cells. Furthermore, the abundance of neurons is positively associated with clinical outcomes in gliomas, while the enrichment of immune and stromal cells has a negative association with them. Our classification method provides new insights into the tumor biology of gliomas, as well as clinical implications for the precise management of this disease.

Shedding light on PRAME expression in dysplastic nevi: a cohort study

Dysplastic nevi represent one of the least agreed-upon entities in dermatopathology despite the existence of established criteria. This study explores preferentially expressed antigen in melanoma (PRAME) in dysplastic nevi, an uncharted area. We examined 22 common melanocytic nevi (CMN), 20 cutaneous melanomas (CM), 48 low-grade dysplastic nevi (LG-DN), and 40 high-grade dysplastic nevi (HG-DN). PRAME was immunohistochemically assessed using a five-tiered system (0 to 4 +). Among CMN, 59% scored 0, 32% scored 1 + , and 9% scored 2 + . CM had score 2 + and 4 + in 11% and 89% of cases, respectively. Among LG-DN, 38% presented score 0, 31% score 1 + , 17% score 2 + , 8% score 3 + , and 6% score 4 + . Thirty per cent of HG-DN demonstrated a score 0, 30% with score 1 + , 15% score 2 + , 10% score 3 + , and 15% score 4 + . Compared to CMN and CM, LG-DN and HG-DN showed heterogeneous expression profiles of PRAME. PRAME positivity effectively distinguished HG-DN from CM with 85% specificity and 80% sensitivity (p < 0.0001). Predictive values were 87% (negative) and 76% (positive). Furthermore, a trend of increased PRAME expression from LG-DN to HG-DN was observed. However, the applicability of PRAME in the differential diagnosis of dysplastic lesions remains unclear as can yield conflicting results with morphology, which remains the primary diagnostic tool for melanocytic lesions.

Molecular subtyping of skin cutaneous melanoma based on inflammatory response

The inflammatory response plays a crucial role in determining the prognosis and therapeutic response of skin cutaneous melanoma (SKCM). However, the molecular subtypes based on the inflammatory response and their clinical significance in SKCM have not been extensively studied. Clustering analyses to identify inflammation subtypes of SKCM based on the expression levels of inflammation response gene. We identified three subtypes: Inflammation_H, Inflammation_M, and Inflammation_L, which offer a more nuanced understanding of the complex relationship between inflammation and SKCM. The Inflammation_H subtype is associated with the most favourable prognosis, and is characterised by high levels of immune infiltrates and PD-L1 expression, low levels of stemness, high differentiation, and high genomic stability. In contrast, the Inflammation_L subtype has the least favourable prognosis, with the lowest levels of immune infiltrates and PD-L1 expression, high levels of stemness, low differentiation, and low genomic stability. In addition, the Inf-score, which is a linear risk scoring model based on the expression levels of inflammatory response genes, can be a useful tool for clinicians to assess SKCM prognosis and guide therapeutic decisions. This scoring model shows promise for clinical use in predicting patient outcomes and helps clinicians tailor treatments for individual patients. In conclusion, these findings represent a significant contribution to our understanding of the molecular subtypes of SKCM based on the levels of inflammatory response genes and their potential clinical significance. However, further studies are necessary to validate these findings and explore the underlying mechanisms of different subtypes.

Estrogen Receptor Expression in DICER1-related Lesions is Associated With the Presence of Cystic Components

DICER1 tumor predisposition syndrome results from pathogenic variants in DICER1 and is associated with a variety of benign and malignant lesions, typically involving kidney, lung, and female reproductive system. Over 70% of sarcomas in DICER1 tumor predisposition syndrome occur in females. Notably, pediatric cystic nephroma (pCN), a classic DICER1 tumor predisposition syndrome lesion, shows estrogen receptor (ER) expression in stromal cells. There are also renal, hepatic, and pancreatic lesions unassociated with DICER1 tumor predisposition syndrome that have an adult female predominance and are characterized/defined by ER-positive stromal cells. Except for pCN, the expression of ER in DICER1-associated lesions remains uninvestigated. In the present study, ER expression was assessed by immunohistochemistry in 89 cases of DICER1-related lesions and 44 lesions lacking DICER1 pathogenic variants. Expression was seen in stromal cells in pCN and pleuropulmonary blastoma (PPB) types I and Ir, whereas anaplastic sarcoma of kidney and PPB types II and III were typically negative, as were other solid tumors of non-Müllerian origin. ER expression was unrelated to the sex or age of the patient. Expression of ER showed an inverse relationship to preferentially expressed antigen in melanoma (PRAME) expression; as lesions progressed from cystic to solid (pCN/anaplastic sarcoma of kidney, and PPB types I to III), ER expression was lost and (PRAME) expression increased. Thus, in DICER1 tumor predisposition syndrome, there is no evidence that non-Müllerian tumors are hormonally driven and antiestrogen therapy is not predicted to be beneficial. Lesions not associated with DICER1 pathogenic variants also showed ER-positive stromal cells, including cystic pulmonary airway malformations, cystic renal dysplasia, and simple renal cysts in adult kidneys. ER expression in stromal cells is not a feature of DICER1 perturbation but rather is related to the presence of cystic components.

Immunotherapeutic Strategies Targeting Breast Cancer Stem Cells

Breast cancer is the most commonly diagnosed cancer in women and is a leading cause of cancer death in women worldwide. Despite the implementation of multiple treatment options, including immunotherapy, breast cancer treatment remains a challenge. In this review, we aim to summarize present challenges in breast cancer immunotherapy and recent advancements in overcoming treatment resistance. We elaborate on the inhibition of signaling cascades, such as the Notch, Hedgehog, Hippo, and WNT signaling pathways, which regulate the self-renewal and differentiation of breast cancer stem cells and, consequently, disease progression and survival. Cancer stem cells represent a rare population of cancer cells, likely originating from non-malignant stem or progenitor cells, with the ability to evade immune surveillance and develop resistance to immunotherapeutic treatments. We also discuss the interactions between breast cancer stem cells and the immune system, including potential agents targeting breast cancer stem cell-associated signaling pathways, and provide an overview of the emerging approaches to breast cancer stem cell-targeted immunotherapy. Finally, we consider the development of breast cancer vaccines and adoptive cellular therapies, which train the immune system to recognize tumor-associated antigens, for eliciting T cell-mediated responses to target breast cancer stem cells.

A novel immune-related long noncoding RNA (lncRNA) pair model to predict the prognosis of triple-negative breast cancer

Background

Breast cancer (BC) is the most prevalent cancer type and is the principal cause of cancer-related death in women. Anti-programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1) immunotherapy has shown promising effects in metastatic triple-negative breast cancer (TNBC), but the potential factors affecting its efficacy have not been elucidated. Immune-related long noncoding RNAs (irlncRNAs) have been reported to be involved in immune escape to influence the carcinogenic process through the PD-1/PD-L1 signaling pathway. Therefore, exploring the potential regulatory mechanism of irlncRNAs in PD-1/PD-L1 immunotherapy in TNBC is of great importance.

Methods

We retrieved transcriptome profiling data from The Cancer Genome Atlas (TCGA) and identified differentially expressed irlncRNA (DEirlncRNA) pairs. Least absolute shrinkage and selection operator (LASSO) regression analysis was performed to construct a risk assessment model.

Results

Receiver operating characteristic (ROC) curve analysis indicated that the risk model may serve as a potential prediction tool in TNBC patients. Clinical stage and risk score were proved to be independent prognostic predictors by univariate and multivariate Cox regression analyses. Subsequently, we investigated the correlation between the risk model and tumor-infiltrating immune cells and immune checkpoints. Finally, we identified USP30-AS1 through the StarBase and Multi Experiment Matrix (MEM) databases, predicted the potential target genes of USP30-AS1, and then discovered that these target genes were closely associated with immune responses.

Conclusions

Our study constructed a risk assessment model by irlncRNA pairs regardless of expression levels, which contributed to predicting the efficacy of immunotherapy in TNBC. Furthermore, the lncRNA USP30-AS1 in the model was positively correlated with the expression of PD-L1 and provided a potential therapeutic target for TNBC.

Early-stage triple negative breast cancer: the therapeutic role of immunotherapy and the prognostic value of pathological complete response

Triple negative breast cancer (TNBC) represents an aggressive disease associated with a high risk of recurrence after curative treatment and a poor prognosis in the metastatic setting. Chemotherapy was for years the only treatment available in the early and metastatic setting, due to the lack of actionable targets. Clinical practice has changed following the results obtained with the addition of immunotherapy to standard chemotherapy, the development of novel drugs [i.e. antibody-drug conjugates (ADCs)], and the use of targeted treatments for patients carrying germline pathogenic breast cancer susceptibility genes (BRCA) 1 or BRCA 2 variants. The treatment of early-stage disease has had a shift in clinical practice since July 2021, after the Food and Drug Administration (FDA) approval of pembrolizumab in association with chemotherapy as neoadjuvant treatment for TNBC and as a single agent in the subsequent adjuvant setting. This intensive treatment based on the combination of a poly-chemotherapy and an immune checkpoint inhibitor (ICI) led to the improvement of short- and long-term outcomes, but it has highlighted some new unmet clinical needs in the treatment of early-stage TNBC: the selection of the most effective adjuvant therapy and the integration of pembrolizumab with other therapeutic strategies [capecitabine, poly(ADP-ribose) polymerase (PARP) inhibitors] based on the achievement of pathologic complete response (pCR); the identification of predictive biomarkers to select patients who could most benefit from the addition of ICI, to minimize toxicities and to maximize outcomes; the possibility of de-escalating chemotherapy in favor of immune-combo or novel agents, such as ADCs; the role of immunotherapy in estrogen receptor (ER)-low patients. The advent of immunotherapy not only addresses current challenges in TNBC treatment but also holds the promise of a radical transformation in its therapeutic paradigm, enhancing significantly clinical outcomes and offering new perspectives for patients grappling with this aggressive form of breast cancer.

Tackling suppressive cancer microenvironment by NARF-derived immune modulatory vaccine and its validation using simulation strategies

Introduction: Targeting tumor microenvironment is beneficial and present an ideal setting for the development of futuristic immunotherapy. Here, we make use of Nuclear prelamin A recognition factor (NARF), a protein linked to the coactivation of transcriptional regulators in human breast cancer stem cells (CSC) in our investigation.

Methods: In this study, we initially computed the epitope regions possessing the ability to stimulate both T and B cells within the NARF protein. These identified epitope areas were fused with an adjuvant such as RpfB and RpfE as well as linkers like AAY, GPGPG, KK, and EAAAK. The constructed vaccine was further characterized by assessing its physicochemical properties and population coverage. The potential interactions of the designed vaccine with different toll-like receptors were examined by a sequence of computational studies. Of note, docking study were employed to understand its mechanism of action. Molecular dynamics and immune simulation studies were conducted to comprehend more into their structural stability and immune responses. The resultant vaccine was back-translated, codon-optimised and introduced into pET-28 (+) vector.

Results and discussion: We hypothesize from the results that the designed NARF protein-based vaccine in our analysis could effectively provoke the immune responses in the target organism through TLR-7 binding and promotes MHC class-II mediated antigen presentation. Indeed, comprehensive evaluations conducted in both in vitro and in vivo settings are imperative to substantiate the safety and efficacy of the developed vaccine.

Tunable PhenoCycler imaging of the murine pre-clinical tumour microenvironments

BACKGROUND

The tumour microenvironment (TME) consists of tumour-supportive immune cells, endothelial cells, and fibroblasts. PhenoCycler, a high-plex single cell spatial biology imaging platform, is used to characterize the complexity of the TME. Researchers worldwide harvest and bank tissues from mouse models which are employed to model a plethora of human disease. With the explosion of interest in spatial biology, these panoplies of archival tissues provide a valuable resource to answer new questions. Here, we describe our protocols for developing tunable PhenoCycler multiplexed imaging panels and describe our open-source data analysis pipeline. Using these protocols, we used PhenoCycler to spatially resolve the TME of 8 routinely employed pre-clinical models of lymphoma, breast cancer, and melanoma preserved as FFPE.

RESULTS

Our data reveal distinct TMEs in the different cancer models that were imaged and show that cell-cell contacts differ depending on the tumour type examined. For instance, we found that the immune infiltration in a murine model of melanoma is altered in cellular organization in melanomas that become resistant to αPD-1 therapy, with depletions in a number of cell-cell interactions.

CONCLUSIONS

This work presents a valuable resource study seamlessly adaptable to any field of research involving murine models. The methodology described allows researchers to address newly formed hypotheses using archival materials, bypassing the new to perform new mouse studies.

Proteogenomic characterization of small cell lung cancer identifies biological insights and subtype-specific therapeutic strategies

We performed comprehensive proteogenomic characterization of small cell lung cancer (SCLC) using paired tumors and adjacent lung tissues from 112 treatment-naive patients who underwent surgical resection. Integrated multi-omics analysis illustrated cancer biology downstream of genetic aberrations and highlighted oncogenic roles of FAT1 mutation, RB1 deletion, and chromosome 5q loss. Two prognostic biomarkers, HMGB3 and CASP10, were identified. Overexpression of HMGB3 promoted SCLC cell migration via transcriptional regulation of cell junction-related genes. Immune landscape characterization revealed an association between ZFHX3 mutation and high immune infiltration and underscored a potential immunosuppressive role of elevated DNA damage response activity via inhibition of the cGAS-STING pathway. Multi-omics clustering identified four subtypes with subtype-specific therapeutic vulnerabilities. Cell line and patient-derived xenograft-based drug tests validated the specific therapeutic responses predicted by multi-omics subtyping. This study provides a valuable resource as well as insights to better understand SCLC biology and improve clinical practice.

Deep learning and transfer learning identify breast cancer survival subtypes from single-cell imaging data

BACKGROUND

Single-cell multiplex imaging data have provided new insights into disease subtypes and prognoses recently. However, quantitative models that explicitly capture single-cell resolution cell-cell interaction features to predict patient survival at a population scale are currently missing.

METHODS

We quantified hundreds of single-cell resolution cell-cell interaction features through neighborhood calculation, in addition to cellular phenotypes. We applied these features to a neural-network-based Cox-nnet survival model to identify survival-associated features. We used non-negative matrix factorization (NMF) to identify patient survival subtypes. We identified atypical subpopulations of triple-negative breast cancer (TNBC) patients with moderate prognosis and Luminal A patients with poor prognosis and validated these subpopulations by label transferring using the UNION-COM method.

RESULTS

The neural-network-based Cox-nnet survival model using all cellular phenotype and cell-cell interaction features is highly predictive of patient survival in the test data (Concordance Index > 0.8). We identify seven survival subtypes using the top survival features, presenting distinct profiles of epithelial, immune, and fibroblast cells and their interactions. We reveal atypical subpopulations of TNBC patients with moderate prognosis (marked by GATA3 over-expression) and Luminal A patients with poor prognosis (marked by KRT6 and ACTA2 over-expression and CDH1 under-expression). These atypical subpopulations are validated in TCGA-BRCA and METABRIC datasets.

CONCLUSIONS

This work provides an approach to bridge single-cell level information toward population-level survival prediction.

TAZ facilitates breast tumor growth by promoting an immune-suppressive tumor microenvironment

The core Hippo pathway module consists of a tumour-suppressive kinase cascade that inhibits the transcriptional coactivators Yes-associated protein (YAP) and WW domain-containing transcription regulator protein 1 (WWTR1; also known as TAZ). When the Hippo pathway is downregulated, as often occurs in breast cancer, YAP/TAZ activity is induced. To elaborate the roles of TAZ in triple-negative breast cancer (TNBC), we depleted Taz in murine TNBC 4T1 cells, using either CRISPR/Cas9 or small hairpin RNA (shRNA). TAZ-depleted cells and their controls, harbouring wild-type levels of TAZ, were orthotopically injected into the mammary fat pads of syngeneic BALB/c female mice, and mice were monitored for tumour growth. TAZ depletion resulted in smaller tumours compared to the tumours generated by control cells, in line with the notion that TAZ functions as an oncogene in breast cancer. Tumours, as well as their corresponding in vitro cultured cells, were then subjected to gene expression profiling by RNA sequencing (RNA-seq). Interestingly, pathway analysis of the RNA-seq data indicated a TAZ-dependent enrichment of 'Inflammatory Response', a pathway correlated with TAZ expression levels also in human breast cancer tumours. Specifically, the RNA-seq analysis predicted a significant depletion of regulatory T cells (Tregs) in TAZ-deficient tumours, which was experimentally validated by the staining of tumour sections and by quantitative cytometry by time of flight (CyTOF). Strikingly, the differences in tumour size were completely abolished in immune-deficient mice, demonstrating that the immune-modulatory capacity of TAZ is critical for its oncogenic activity in this setting. Cytokine array analysis of conditioned medium from cultured cells revealed that TAZ increased the abundance of a small group of cytokines, including plasminogen activator inhibitor 1 (Serpin E1; also known as PAI-1), CCN family member 4 (CCN4; also known as WISP-1) and interleukin-23 (IL-23), suggesting a potential mechanistic explanation for its in vivo immunomodulatory effect. Together, our results imply that TAZ functions in a non-cell-autonomous manner to modify the tumour immune microenvironment and dampen the anti-tumour immune response, thereby facilitating tumour growth.

Differential regulation of fibronectin expression and fibrillogenesis by autocrine TGF-β1 signaling in malignant and benign mammary epithelial cells

Remodeling of the extracellular matrix (ECM) is a key hallmark of cancer progression. A critical component of ECM remodeling is the assembly of the glycoprotein fibronectin (FN) into insoluble fibrils, which provide a scaffold for invading vascular endothelial cells and escaping cancer cells, as well as a framework for collagen deposition and oncogenic cytokine tethering. FN fibril assembly is induced by Transforming Growth Factor-β1 (TGF-β1), which was originally identified for its role in malignant transformation. Addition of exogenous TGF-β1 drives FN fibril assembly while also upregulating endogenous TGF-β1 expression and autocrine signaling. In the current study, we sought to determine if autocrine TGF-β1 signaling plays a role in FN fibril formation in either MCF10A mammary epithelial cells, which behave similarly to healthy epithelia, or malignant MDA- MB-231 breast cancer cells. Our results show two interesting findings: first, malignant MDA-MB- 231 cells assemble less FN into fibrils, despite expressing and secreting more soluble FN; second, autocrine TGF-β1 signaling is required for FN fibril formation in MCF10A epithelial cells, even in the presence of exogenous, active TGF-β1. This suggests that autocrine TGF-β1 is signaling through distinct pathways from active exogenous TGF-β1. We hypothesized that this signaling was mediated by interactions between the TGF-β1 latency associated peptide (LAP) and αv integrins; indeed, incubating MCF10As with soluble LAP, even in the absence of the active TGF-β1 ligand, partially recovered FN fibril assembly. Taken together, these data suggests that autocrine TGF-β1 plays a critical role in FN fibril assembly, and this interaction is mediated by LAP-integrin signaling.

Immunosignatures associated with TP53 status and co-mutations classify prognostically head and neck cancer patients

BACKGROUND

Immune checkpoint inhibitors (ICIs) are a therapeutic strategy for various cancers although only a subset of patients respond to the therapy. Identifying patients more prone to respond to ICIs may increase the therapeutic benefit and allow studying new approaches for resistant patients.

METHODS

We analyzed the TCGA cohort of HNSCC patients in relation to their activation of 26 immune gene expression signatures, as well as their cell type composition, in order to define signaling pathways associated with resistance to ICIs. Results were validated on two cohorts of 102 HNSCC patients and 139 HNSCC patients under treatment with PD-L1 inhibitors, respectively, and a cohort of 108 HNSCC HPV negative patients and by in vitro experiments in HNSCC cell lines.

RESULTS

We observed a significant association between the gene set and TP53 gene status and OS and PFS of HNSCC patients. Surprisingly, the presence of a TP53 mutation together with another co-driver mutation was associated with significantly higher levels of the immune gene expression, in comparison to tumors in which the TP53 gene was mutated alone. In addition, the higher level of TP53 mutated-dependent MYC signature was associated with lower levels of the immune gene expression signature. In vitro and three different patient cohorts validation analyses corroborated these findings.

CONCLUSIONS

Immune gene signature sets associated with TP53 status and co-mutations classify with more accuracy HNSCC patients. These biomarkers may be easily implemented in clinical setting.

Neoadjuvant Immunotherapy in Early, Triple-Negative Breast Cancers: Catching Up with the Rest

Despite breast cancer being long thought to be "immunologically cold," within early, triple-negative breast cancer (TNBC), there has been exciting advances with the use of immune checkpoint modulation combined with neoadjuvant chemotherapy. We review the major trials that have investigated combination immunochemotherapy in the neoadjuvant setting, reviewing both the pathological complete response rates and the maturing data regarding event-free and overall survival. Strategies to deescalate adjuvant therapy in patients with preserving excellent clinical outcome, as well as exploration of combinatorial adjuvant therapies to improve outcome in those with extensive residual are the next-generation challenges. In addition to refinement of existing biomarkers, such as PD-L1, TILs, and tumor mutational burden (TMB), exploration of topics like the microbiome as both a biomarker and a therapeutic has shown promise in other cancer types, which motivates investigating these in breast cancer.

In vitro evaluation of the anti‑breast cancer properties and gene expression profiles of Thai traditional formulary medicine extracts

Breast cancer is a leading cause of cancer-related deaths worldwide. Moreover, standard treatments are limited, so new alternative treatments are required. Thai traditional formulary medicine (TTFM) utilizes certain herbs to treat different diseases due to their dominant properties including anti-fungal, anti-bacterial, antigenotoxic, anti-inflammatory and anti-cancer actions. However, very little is known about the anti-cancer properties of TTFM against breast cancer cells and the underlying molecular mechanism has not been elucidated. Therefore, the present study, evaluated the metabolite profiles of TTFM extracts, the anti-cancer activities of TTFM extracts, their effects on the apoptosis pathway and associated gene expression profiles. Liquid chromatography with tandem mass spectroscopy analysis identified a total of 226 compounds within the TTFM extracts. Several of these compounds have been previously shown to have an anti-cancer effect in certain cancer types. The MTT results demonstrated that the TTFM extracts significantly reduced the cell viability of the breast cancer 4T1 and MDA-MB-231 cell lines. Moreover, an apoptosis assay, demonstrated that the TTFM extracts significantly increased the proportion of apoptotic cells. Furthermore, the RNA-sequencing results demonstrated that 25 known genes were affected by TTFM treatment in 4T1 cells. TTFM treatment significantly up-regulated Slc5a8 and Arhgap9 expression compared with untreated cells. Moreover, Cybb, and Bach2os were significantly downregulated after TTFM treatment compared with untreated cells. Reverse transcription-quantitative PCR demonstrated that TTFM extract treatment significantly increased Slc5a8 and Arhgap9 mRNA expression levels and significantly decreased Cybb mRNA expression levels. Moreover, the mRNA expression levels of Bax and Casp9 were significantly increased after TTFM treatment in 4T1 cells compared with EpH4-Ev cells. These findings indicated anti-breast cancer activity via induction of the apoptotic process. However, further experiments are required to elucidate how TTFM specifically regulates genes and proteins. This study supports the potential usage of TTFM extracts for the development of anti-cancer drugs.

Identification of key claudin genes associated with survival prognosis and diagnosis in colon cancer through integrated bioinformatic analysis

The claudin multigene family is associated with various aberrant physiological and cellular signaling pathways. However, the association of claudins with survival prognosis, signaling pathways, and diagnostic efficacy in colon cancer remains poorly understood. Methods: Through the effective utilization of various bioinformatics methods, including differential gene expression analysis, gene set enrichment analysis protein-protein interaction (PPI) network analysis, survival analysis, single sample gene set enrichment analysis (ssGSEA), mutational variance analysis, and identifying receiver operating characteristic curve of claudins in The Cancer Genome Atlas colon adenocarcinoma (COAD). Results: We found that: CLDN2, CLDN1, CLDN14, CLDN16, CLDN18, CLDN9, CLDN12, and CLDN6 are elevated in COAD. In contrast, the CLDN8, CLDN23, CLDN5, CLDN11, CLDN7, and CLDN15 are downregulated in COAD. By analyzing the public datasets GSE15781 and GSE50760 from NCBI-GEO (https://www.ncbi.nlm.nih.gov/geo/), we have confirmed that CLDN1, CLDN2, and CLDN14 are significantly upregulated and CLDN8 and CLDN23 are significantly downregulated in normal colon, colon adenocarcinoma tumor, and liver metastasis of colon adenocarcinoma tissues from human samples. Various claudins are mutated and found to be associated with diagnostic efficacy in COAD. Conclusion: The claudin gene family is associated with prognosis, immune regulation, signaling pathway regulations, and diagnosis of COAD. These findings may provide new molecular insight into claudins in the treatment of colon cancer.

Deep-learning and transfer learning identify new breast cancer survival subtypes from single-cell imaging data

Quantitative models that explicitly capture single-cell resolution cell-cell interaction features to predict patient survival at population scale are currently missing. Here, we computationally extracted hundreds of features describing single-cell based cell-cell interactions and cellular phenotypes from a large, published cohort of cyto-images of breast cancer patients. We applied these features to a neural-network based Cox-nnet survival model and obtained high accuracy in predicting patient survival in test data (Concordance Index > 0.8). We identified seven survival subtypes using the top survival features, which present distinct profiles of epithelial, immune, fibroblast cells, and their interactions. We identified atypical subpopulations of TNBC patients with moderate prognosis (marked by GATA3 over-expression) and Luminal A patients with poor prognosis (marked by KRT6 and ACTA2 over-expression and CDH1 under-expression). These atypical subpopulations are validated in TCGA-BRCA and METABRIC datasets. This work provides important guidelines on bridging single-cell level information towards population-level survival prediction.

STATEMENT OF TRANSLATIONAL RELEVANCE

Our findings from a breast cancer population cohort demonstrate the clinical utility of using the single-cell level imaging mass cytometry (IMC) data as a new type of patient prognosis prediction marker. Not only did the prognosis prediction achieve high accuracy with a Concordance index score greater than 0.8, it also enabled the discovery of seven survival subtypes that are more distinguishable than the molecular subtypes. These new subtypes present distinct profiles of epithelial, immune, fibroblast cells, and their interactions. Most importantly, this study identified and validated atypical subpopulations of TNBC patients with moderate prognosis (GATA3 over-expression) and Luminal A patients with poor prognosis (KRT6 and ACTA2 over-expression and CDH1 under-expression), using multiple large breast cancer cohorts.

Dysregulated Forkhead Box (FOX) Genes Association with Survival Prognosis, Anti-tumor Immunity, and Key Targeting Drugs in Colon Adenocarcinoma

BACKGROUND

Several studies have revealed that the aberrant expressions of forkhead box (FOX) genes are associated with carcinogenesis. However, the crucial biological functions of the FOX gene in colon adenocarcinoma (COAD) remain unknown.

METHODS

The TCGA-COAD dataset (n=328) was utilized for determining the deregulated FOX genes and their association with functional enrichment, protein-protein interaction (PPI), survival prognosis, anti-tumor immunity, cancer-associated pathways, and biological processes in COAD. In addition, we used GSE166427 (GPL13667) as a validation cohort (n=196). Molecular docking studies were applied to perform the drug interactions.

RESULTS

The FOX genes are deregulated in the COAD (Log2 FC>0.50, P<0.05), and the PPI network of FOX members is substantially related to the enrichment of cancerous signaling, immune responses, and cellular development (FDR<0.05). A worse prognosis for overall survival in COAD individuals is connected with the subgroup of FOX transcripts (P≤0.05). FOXD4, FOXH1, and FOXS1 were identified as predictive variables in the univariate and multivariate Cox regression models (P≤0.05). FOXH1 and FOXS1 are substantially linked to the deregulated immunity in COAD (R>0.20, P<0.01). Furthermore, FOXS1 expression regulates cancer-associated pathways and biological processes (P<0.05). Moreover, FOXD4, FOXH1, and FOXS1 are genetically altered and showed diagnostic efficacy in COAD. We revealed that FOXD4, FOXH1, and FOXS1 are consistently deregulated in GSE166427 (P<0.05). Finally, molecular docking revealed that FOXH1 interacted with various drugs, including belinostat, entinostat, and panobinostat.

CONCLUSION

The FOX genes have a strong correlation with the poor prognosis for survival, tumor immunity, cancer-associated pathways, and biochemical processes that cause the pathogenesis of COAD.

A pairwise immune gene model for predicting overall survival and stratifying subtypes of colon adenocarcinoma

OBJECTIVES

There is increasing evidence for a close correlation between risk stratification, prognosis and the immune environment in colon adenocarcinoma (COAD). However, the efficacy of immunotherapy is different among different patients with COAD. Therefore, the current work tends to use immune-related gene to develop a gene-pair model to evaluate the COAD prognosis, and to develop a new method for risk stratification of COAD, which is conducive to better predict the immunotherapy effect of patients.

METHODS

Specifically, from the TCGA and GEO (GSE14333 and GSE39582) databases, we first collected gene expression profiles, associated survival follow-up information of COAD patients. Through systematic bioinformatics analysis, we established a prognosis-related model of colon cancer with three pairs of "immune gene pairs", with uni- and multivariate and lasso cox regression analyses verifying the model stability. Most immune cells showed markedly different levels of infiltration between the two risk subgroups calculated by the model. More, single-cell RNA-seq analyses were also performed to validate the selected genes in the immune gene-pair model.

RESULTS

A prognosis-related model of colon cancer with three pairs of "immune gene pairs" were built and validated by several datasets. The analysis of immune landscape of COAD revealed that low-risk subgroup obtained by the prognosis-related model for COAD can be further divided into three subclusters with different prognosis. Then, we applied the Tumor online Prognostic analyses Platform (ToPP) to construct a prognostic model using these five genes. Results show that APOD, ISG20 and STC2 are risk factors, while CXCL9 and IL7R are protection factors. We also found that only the five-gene model could also predict the prognosis of COAD patients, indicating the robustness of the gene-pair model. Among the five genes, including CXCL9, APOD, STC2, ISG20, and IL7R, in the gene-pair model, single-cell RNA sequencing reveals the high expression of CXCL9 and IL7R in inflammatory macrophages. Using cell-cell interaction and trajectory analysis, data indicate that CXCL9+/IL7R+ pro-inflammatory macrophages were capable of secreting and activating more anti-tumor pathways than CXCL9-/IL7R- pro-inflammatory macrophages.

CONCLUSIONS

In short, we have successfully developed an "immune gene pair" related model that can judge the prognostic status of patients with COAD and may contribute to risk stratification and evaluate potential beneficiaries of immunotherapy, providing new ideas for the anti-COAD management and therapy.

Deconvolution of cancer cell states by the XDec-SM method

Proper characterization of cancer cell states within the tumor microenvironment is a key to accurately identifying matching experimental models and the development of precision therapies. To reconstruct this information from bulk RNA-seq profiles, we developed the XDec Simplex Mapping (XDec-SM) reference-optional deconvolution method that maps tumors and the states of constituent cells onto a biologically interpretable low-dimensional space. The method identifies gene sets informative for deconvolution from relevant single-cell profiling data when such profiles are available. When applied to breast tumors in The Cancer Genome Atlas (TCGA), XDec-SM infers the identity of constituent cell types and their proportions. XDec-SM also infers cancer cells states within individual tumors that associate with DNA methylation patterns, driver somatic mutations, pathway activation and metabolic coupling between stromal and breast cancer cells. By projecting tumors, cancer cell lines, and PDX models onto the same map, we identify in vitro and in vivo models with matching cancer cell states. Map position is also predictive of therapy response, thus opening the prospects for precision therapy informed by experiments in model systems matched to tumors in vivo by cancer cell state.

TimiGP: Inferring cell-cell interactions and prognostic associations in the tumor immune microenvironment through gene pairs

Determining the prognostic association of different immune cell types in the tumor microenvironment is critical for understanding cancer biology and developing new therapeutic strategies. However, this is challenging in certain cancer types, where the abundance of different immune subsets is highly correlated. In this study, we develop a computational method named TimiGP to overcome this challenge. Based on bulk gene expression and survival data, TimiGP infers cell-cell interactions that reveal the association between immune cell relative abundance and prognosis. As demonstrated in metastatic melanoma, TimiGP prioritizes immune cells critical in prognosis based on the identified cell-cell interactions. Highly consistent results are obtained by TimiGP when applied to seven independent melanoma datasets and when different cell-type marker sets are used as inputs. Additionally, TimiGP can leverage single-cell RNA sequencing data to delineate the tumor immune microenvironment at high resolutions across a wide range of cancer types.

Characterization of the immune environment in pregnancy-associated breast cancer

Pregnancy-associated breast cancer (PrBC) is a rare and clinically challenging condition. Specific immune mechanisms and pathways are involved in maternal-fetal tolerance and tumor-host immunoediting. The comprehension of the molecular processes underpinning this immune synergy in PrBC is needed to improve patients' clinical management. Only a few studies focused on the immune biology of PrBC and attempted to identify bona fide biomarkers. Therefore, clinically actionable information remains extremely puzzling for these patients. In this review article, we discuss the current knowledge on the immune environment of PrBC, in comparison with pregnancy-unrelated breast cancer and in the context of maternal immune changes during pregnancy. A particular emphasis is given to the actual role of potential immune-related biomarkers for PrBC clinical management.

Gene set enrichment analysis identifies immune subtypes of kidney renal clear cell carcinoma with significantly different molecular and clinical properties

Background

Kidney renal clear cell carcinoma (KIRC) is the most prevalent renal malignancy, marked by a high abundance of tumor-infiltrating lymphocytes (TILs) and an unfavorable prognosis upon metastasis. Numerous studies have demonstrated that KIRC possesses a tumor microenvironment that is highly heterogeneous, and this is associated with significant variations in the effectiveness of most first-line drugs administered to KIRC patients. Therefore, it is crucial to classify KIRC based on the tumor microenvironment, although these subtyping techniques are still inadequate.

Methods

By applying gene set enrichment scores of 28 immune signatures, we conducted a hierarchical clustering of KIRC and determined its immune subtypes. In addition, we conducted a comprehensive exploration of the molecular and clinical features of these subtypes, including survival prognosis, proliferation, stemness, angiogenesis, tumor microenvironment, genome instability, intratumor heterogeneity, and pathway enrichment.

Results

Through cluster analysis, two immune subtypes of KIRC were identified and termed Immunity-High (Immunity-H) and Immunity-Low (Immunity-L). This clustering outcome was consistent in four independent KIRC cohorts. The subtype Immunity-H exhibited elevated levels of TILs, tumor aneuploidy, homologous recombination deficiency, stemness, and proliferation potential, along with a poorer prognosis for survival. Despite this, the Immunity-L subtype demonstrated elevated intratumor heterogeneity and a stronger angiogenesis signature in contrast to Immunity-H. According to the results of pathway enrichment analysis, the Immunity-H subtype was found to be highly enriched in immunological, oncogenic, and metabolic pathways, whereas the Immunity-L subtype was highly enriched in angiogenic, neuroactive ligand-receptor interaction, and PPAR pathways.

Conclusions

Based on the enrichment of immune signatures in the tumor microenvironment, KIRC can be categorized into two immune subtypes. The two subtypes demonstrate considerably distinct molecular and clinical features. In KIRC, an increase in immune infiltration is linked to a poor prognosis. Patients with Immunity-H KIRC may exhibit active responses to PPAR and immune checkpoint inhibitors, whereas patients with Immunity-L may manifest favorable responses to anti-angiogenic agents and immune checkpoint inhibitors. The immunological classification provides molecular insights into KIRC immunity, as well as clinical implications for the management of this disease.

Lima JC, Langohr IM, Chouljenko VN, Kousoulas KG. The Oncolytic herpes simplex virus type-1 (HSV-1) vaccine strain VC2 causes intratumor infiltration of functionally active T cells and inhibition of tumor metastasis and pro-tumor genes VEGF and PDL1 expression in the 4T1/Balb/c mouse model of stage four breast cancer

Introduction: Oncolytic viruses (OVs) provide new modalities for cancer therapy either alone or in combination with synergistic immunotherapies and/or chemotherapeutics. Engineered Herpes Simplex Virus Type-1 (HSV-1) has shown strong promise for the treatment of various cancers in experimental animal models as well as in human patients, with some virus strains licensed to treat human melanoma and gliomas. In the present study we evaluated the efficacy of mutant HSV-1 (VC2) in a late stage, highly metastatic 4T1 murine syngeneic. Method: VC2 was constructed VC2 using double red recombination technology. For in-vivo efficacy we utilized a late stage 4T1 syngeneic and immunocompetent BALB/cJ mouse model breast cancer model which exhibits efficient metastasis to the lung and other organs. Results: VC2 replicated efficiently in 4T1 cells and in cell culture, achieving titers similar to those in African monkey kidney (Vero) cells. Intra-tumor treatment with VC2 did not appreciably reduce average primary tumor sizes but a significant reduction of lung metastasis was noted in mice treated intratumorally with VC2, but not with ultraviolet-inactivated VC2. This reduction of metastasis was associated with increased T cell infiltration comprised of CD4+ and CD4+CD8+ double-positive T cells. Characterization of purified tumor infiltrating T cells revealed a significant improvement in their proliferation ability compared to controls. In addition, significant T cell infiltration was observed in the metastatic nodules associated with reduction of pro-tumor PD-L1 and VEGF gene transcription. Conclusion: These results show that VC2 therapy can improve anti-tumor response associated with a better control of tumor metastasis. improve T cell responses and reduce pro-tumor biomarker gene transcription. VC2 holds promise for further development as an oncolytic and immunotherapeutic approach to treat breast and other cancers.

Pan-cancer analysis of TASL: a novel immune infiltration-related biomarker for tumor prognosis and immunotherapy response prediction

BACKGROUND

New immunotherapeutic strategies based on predictors are urgently needed. Toll-like receptor adaptor interacting with SLC15A4 on the lysosome (TASL) was recently confirmed to fulfill an important role in the innate immune response. However, whether TASL is involved in tumor development and immunotherapy response prediction has not been reported.

METHODS

TCGA and GTEx were used to yield transcriptional, genetic, and epigenetic levels of TASL in 33 cancer types. CIBERSORT was used to explore the correlation between TASL expression and multiple immune-related signatures and tumor-infiltrating immune cell content in different cancer types. The ability of TASL to predict tumor immunotherapy response was analyzed in seven datasets. Finally, we tested TASL expression in human glioma cell lines and tissue samples and analyzed its correlation with clinicopathological parameters.

RESULTS

TASL is widely heterogeneous at the transcriptional, genetic, and epigenetic levels. High TASL expression is an independent poor prognostic factor for immune "cold" tumor Low-Grade Glioma (LGG) but an opposite factor for "hot" tumors Lung Adenocarcinoma (LUAD) and Skin Cutaneous Melanoma (SKCM). TASL may affect tumor immune infiltration by mediating tumor-infiltrating lymphocytes and tumor-associated macrophages. It may differentially affect the prognosis of the three cancers by regulating the immunosuppressive microenvironment in LGG and the immunostimulatory microenvironment in LUAD and SKCM. High TASL expression is a potential biomarker for the positive response to immunotherapy in cancers such as SKCM and was also experimentally confirmed to be positively associated with adverse clinicopathological features of gliomas.

CONCLUSION

TASL expression is an independent prognostic factor for LGG, LUAD, and SKCM. High TASL expression is a potential biomarker for the positive response to immunotherapy in certain cancer types such as SKCM. Further basic studies focusing on TASL expression and tumor immunotherapy are urgently needed.

Progress and Challenges of Immunotherapy Predictive Biomarkers for Triple Negative Breast Cancer in the Era of Single-Cell Multi-Omics

Triple-negative breast cancer (TNBC) is a highly aggressive subtype of breast cancer with a poor prognosis. Despite conventional treatments, including surgery, radiation, and chemotherapy, the overall response rate to PD-1/PD-L1 immune checkpoint inhibitors remains low, with limited predictive significance from current biomarkers such as PD-L1 expression, tumor-infiltrating lymphocytes (TILs), and tumor mutational burden (TMB). To address this challenge, recent advancements in single-cell sequencing techniques have enabled deeper exploration of the highly complex and heterogeneous TNBC tumor microenvironment at the single-cell level, revealing promising TNBC predictive biomarkers for immune checkpoint inhibitors. In this review, we discuss the background, motivation, methodology, results, findings, and conclusion of multi-omics analyses that have led to the identification of these emerging biomarkers. Our review suggests that single-cell multi-omics analysis holds great promise for the identification of more effective biomarkers and personalized treatment strategies for TNBC patients.

Narrative review on the role of immunotherapy in early triple negative breast cancer: unveiling opportunities and overcoming challenges

Background and Objective

Triple negative breast cancer (TNBC) represents a highly aggressive breast cancer subtype, historically managed with chemotherapy regimens predominantly involving anthracyclines and taxanes, yielding unfavorable prognoses. This review endeavors to offer a thorough examination of the present state of treatment strategies for early stage triple negative breast cancer (eTNBC), with a particular emphasis on immunotherapy modalities, combination therapies, predictive biomarkers, and ongoing clinical trials. The principal aim of this review is to meticulously assess the available literature, ascertain significant discoveries, and engage in discussions regarding their potential implications for future research endeavors, clinical applications, and policy formulation.

Methods

This review was conducted using PubMed and Google Scholar databases, with the latest update performed in March 2023. The search strategy was designed to ensure a comprehensive analysis of the literature, with a focus on recent advancements.

Key Content and Findings

We critically assess the current eTNBC treatment landscape, covering efficacy and limitations of monotherapy, combination therapies, and predictive biomarkers. We highlight promising results from recent trials, address controversies surrounding chemotherapy, and explore optimal approaches for adjuvant and neoadjuvant therapy (NAT). Insights into personalized treatment strategies, ongoing trials, and future perspectives are provided, advancing our understanding of therapeutic options for eTNBC.

Conclusions

Through a comprehensive analysis of the literature, this review highlights the potential of immunotherapy, particularly in combination with chemotherapy, as a promising approach for treating eTNBC. However, further research is warranted to optimize treatment strategies, refine patient selection criteria, and identify reliable biomarkers for predicting response to immune checkpoint inhibitors (ICIs). The findings of this review hold significant implications for future research, clinical practice, and policy-making, offering valuable insights into the current challenges and advancements in eTNBC treatment. Ultimately, this knowledge can contribute to improved patient outcomes, enhanced quality of life, and the development of more effective therapeutic approaches for eTNBC.

Syndecan-1 as an immunogene in Triple-negative breast cancer: regulation tumor-infiltrating lymphocyte in the tumor microenviroment and EMT by TGFb1/Smad pathway

BACKGROUND

Immune checkpoint inhibitors are the most studied forms of immunotherapy for triple-negative breast cancer (TNBC). The Cancer Genome Map (TCGA) and METABRIC project provide large-scale cancer samples that can be used for comprehensive and reliable immunity-related gene research.

METHODS

We analyzed data from TCGA and METABRIC and established an immunity-related gene prognosis model for breast cancer. The SDC1 expression in tumor and cancer associated fibroblasts (CAFs) was then observed in 282 TNBC patients by immunohistochemistry. The effects of SDC1 on MDA-MB-231 proliferation, migration and invasion were evaluated. Qualitative real-time PCR and western blotting were performed to identify mRNA and protein expression, respectively.

RESULTS

SDC1, as a key immunity-related gene, was significantly correlated with survival in the TCGA and METABRIC databases, while SDC1 was found to be highly expressed in TNBC in the METABRIC database. In the TNBC cohort, patients with high SDC1 expression in tumor cells and low expression in CAFs had significantly lower disease-free survival (DFS) and fewer tumor-infiltrating lymphocytes (TILs). The downregulation of SDC1 decreased the proliferation of MDA-MB-231, while promoting the migration of MDA-MB-231 cells by reducing the gene expression of E-cadherin and TGFb1 and activating p-Smad2 and p-Smad3 expression.

CONCLUSION

SDC1 is a key immunity-related gene that is highly expressed TNBC patients. Patients with high SDC1 expression in tumors and low expression in CAFs had poor prognoses and low TILs. Our findings also suggest that SDC1 regulates the migration of MDA-MB-231 breast cancer cells through a TGFb1-Smad and E-cadherin-dependent mechanism.

Integrated bioinformatics analyses identifying key transcriptomes correlated with prognosis and immune infiltrations in lung squamous cell carcinoma

Background

Lung Squamous Cell Carcinoma (LUSC) is a major subtype of lung malignancies and is associated with the cause of cancer-mediated mortality worldwide. However, identification of transcriptomic signatures associated with survival-prognosis and immunity of tumor remains lacking.

Method

The GSE2088, GSE6044, GSE19188, GSE21933, GSE33479, GSE33532, and GSE74706 were integrated for identifying differentially expressed genes (DEGs) with combined effect sizes. Also, the TCGA LUSC cohort was used for further analysis. A series of bioinformatics methods were utilized for conducting the whole study.

Results

The 831 genes (such as DSG3, PKP1, DSC3, TPX2, and UBE2C) were found upregulated and the 731 genes (such as ABCA8, SELENBP1, FAM107A, and CACNA2D2) were downregulated in the LUSC. The functional enrichment analysis identifies the upregulated KEGG pathways, including cell cycle, DNA replication, base excision repair, proteasome, mismatch repair, and cellular senescence. Also, the key hub genes (such as EGFR, HRAS, JUN, CDH1, BRCA1, CASP3, RHOA, HDAC1, HIF1A, and CCNA2) were identified along with the eight gene modules that were significantly related to the protein-protein interaction (PPI). The clinical analyses identified that the overexpression group of CDH3, PLAU, PKP3, STIL, CALU, LOXL2, POSTN, DPP3, GALNT2, LOX, and ITPA are substantially associated with a poor survival prognosis and the downregulated group of IL18R1 showed a similar trend. Moreover, our investigation demonstrated that the survival-associated genes were correlated with the stromal and immune scores in LUSC, indicating that the survival-associated genes regulate tumor immunity. The survival-associated genes were genetically altered in 27% of LUSC patients and showed excellent diagnostic efficiency. Finally, the consistent expression level of CDH3, PLAU, PKP3, STIL, CALU, LOXL2, POSTN, DPP3, GALNT2, and ITPA were found in the TCGA LUSC cohort.

Conclusions

The identification of key transcriptomic signatures can be elucidated by the crucial mechanism of LUSC carcinogenesis.

Defining the Emergence of New Immunotherapy Approaches in Breast Cancer: Role of Myeloid-Derived Suppressor Cells

Breast cancer (BC) continues to be the most diagnosed tumor in women and a very heterogeneous disease both inter- and intratumoral, mainly given by the variety of molecular profiles with different biological and clinical characteristics. Despite the advancements in early detection and therapeutic strategies, the survival rate is low in patients who develop metastatic disease. Therefore, it is mandatory to explore new approaches to achieve better responses. In this regard, immunotherapy arose as a promising alternative to conventional treatments due to its ability to modulate the immune system, which may play a dual role in this disease since the relationship between the immune system and BC cells depends on several factors: the tumor histology and size, as well as the involvement of lymph nodes, immune cells, and molecules that are part of the tumor microenvironment. Particularly, myeloid-derived suppressor cell (MDSC) expansion is one of the major immunosuppressive mechanisms used by breast tumors since it has been associated with worse clinical stage, metastatic burden, and poor efficacy of immunotherapies. This review focuses on the new immunotherapies in BC in the last five years. Additionally, the role of MDSC as a therapeutic target in breast cancer will be described.

Immature natural killer cells promote progression of triple-negative breast cancer

Natural killer (NK) cells are cytotoxic lymphocytes that accumulate within the tumor microenvironment and are generally considered to be antitumorigenic. Using single-cell RNA sequencing and functional analysis of multiple triple-negative breast cancer (TNBC) and basal tumor samples, we observed a unique subcluster of Socs3highCD11b-CD27- immature NK cells that were present only in TNBC samples. These tumor-infiltrating NK cells expressed a reduced cytotoxic granzyme signature and, in mice, were responsible for activating cancer stem cells through Wnt signaling. NK cell-mediated activation of these cancer stem cells subsequently enhanced tumor progression in mice, whereas depletion of NK cells or Wnt ligand secretion from NK cells by LGK-974 decreased tumor progression. In addition, NK cell depletion or inhibition of their function improved anti-programmed cell death ligand 1 (PD-L1) antibody or chemotherapy response in mice with TNBC. Furthermore, tumor samples from patients with TNBC and non-TNBC revealed that increased numbers of CD56bright NK cells were present in TNBC tumors and were correlated to poor overall survival in patients with TNBC. Together, our findings identify a population of protumorigenic NK cells that may be exploited for both diagnostic and therapeutic strategies to improve outcomes for patients with TNBC.

The New Frontier of Immunotherapy: Chimeric Antigen Receptor T (CAR-T) Cell and Macrophage (CAR-M) Therapy against Breast Cancer

Breast cancer represents one of the most common tumor histologies. To date, based on the specific histotype, different therapeutic strategies, including immunotherapies, capable of prolonging survival are used. More recently, the astonishing results that were obtained from CAR-T cell therapy in haematological neoplasms led to the application of this new therapeutic strategy in solid tumors as well. Our article will deal with chimeric antigen receptor-based immunotherapy (CAR-T cell and CAR-M therapy) in breast cancer.

LAG-3 expression in tumor microenvironment of triple-negative breast cancer

BACKGROUND

This study aimed to evaluate the expression of lymphocyte activation gene-3 (LAG-3) and its relationship with programmed cell death ligand-1 (PD-L1) in triple-negative breast cancer (TNBC).

METHODS

: LAG-3 and PD-L1 was evaluated in tumor-infiltrating lymphocytes (TILs) using immunohistochemistry (IHC). The chi-square test was used to estimate the associations between LAG-3, PD-L1 and clinicopathological characteristics. Correlation between LAG-3 stromal TIL (sTIL), LAG-3 intraepitelial TIL (iTIL) and PD-L1 was assessed with using the Spearman's correlation coefficient. Survival analysis was performed using the Kaplan-Meier method.

RESULTS

The percentages of LAG-3 sTIL+, LAG-3 iTIL+, PD-L1+ tumor cells and PD-L1+ inflammatory cells were 52%, 42%, 14% and 70%, respectively. A strong positive correlation between LAG-3 sTIL and LAG-3 iTIL (r = 0.874, p < 0.001) and a moderate positive correlation between LAG-3 sTIL and PD-L1 (r = 0.584, p < 0.001) were found. LAG-3 and PD-L1 status did not significantly affect overall survival (OS) (HR: 0.56 (95% CI: 0.15-2.11) (p = 0.397), HR: 2.70 (95% CI: 0.56-13.02) (p = 0.215), respectively).

DISCUSSION

High levels of LAG-3 and PD-L1 expression were detected in patients with TNBC. Although their contribution to survival could not be determined, the high expression rates of PD-L1 and LAG-3 may help identify the subgroup of TNBC that would benefit from immunotherapy.

Triple negative breast cancer: Immunogenicity, tumor microenvironment, and immunotherapy

Triple negative breast cancer (TNBC) is a biologically diverse subtype of breast cancer characterized by genomic and transcriptional heterogeneity and exhibiting aggressive clinical behaviour and poor prognosis. In recent years, emphasis has been placed on the identification of mechanisms underlying the complex genomic and biological profile of TNBC, aiming to tailor treatment strategies. High immunogenicity, specific immune activation signatures, higher expression of immunosuppressive genes and higher levels of stromal Tumor Infiltrating Lymphocytes, constitute some of the key elements of the immune driven landscape associated with TNBC. The unprecedented response of TNBC to immunotherapy has undoubtedly changed the standard of care in this disease both in the early and the metastatic setting. However, the extent of interplay between immune infiltration and mutational signatures in TNBC is yet to be fully unravelled. In the present review, we present clinical evidence on the immunogenicity and tumour microenvironment influence on TNBC progression and the current treatment paradigms in TNBC based on immunotherapy.

A signature-based classification of lung adenocarcinoma that stratifies tumor immunity

Background

Immune-related subgroup classification in immune checkpoint blockade (ICB) therapy is largely inconclusive in lung adenocarcinoma (LUAD).

Materials and methods

First, the single-sample Gene Set Enrichment Analysis (ssGSEA) and K-means algorithms were used to identify immune-based subtypes for the LUAD cohort based on the immunogenomic profiling of 29 immune signatures from The Cancer Genome Atlas (TCGA) database (n = 504). Second, we examined the prognostic and predictive value of immune-based subtypes using bioinformatics analysis. Survival analysis and additional COX proportional hazards regression analysis were conducted for LUAD. Then, the immune score, tumor-infiltrating immune cells (TIICs), and immune checkpoint expression of the three subtypes were analyzed. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) of the differentially expressed genes (DEGs) between three immune-based subtypes were subsequently analyzed for functional enrichment pathways.

Result

A total of three immune-based subtypes with distinct immune signatures have been identified for LUAD and designated as cluster 1 (C1), cluster 2 (C2), and cluster 3 (C3). Patients in C3 had higher stromal, immune, and ESTIMATE scores, whereas those in C1 had the opposite. Patients in C1 had an enrichment of macrophages M0 and activation of dendritic cells, whereas tumors in C3 had an enrichment of CD8⁺ T cells, activation of CD4⁺ memory T cells, and macrophages M1. C3 had a higher immune cell infiltration and a better survival prognosis than other subtypes. Furthermore, patients in C3 had higher expression levels of immune checkpoint proteins such as PD-L1, PD1, CTLA4, LAG3, IDO1, and HAVCR2. No significant differences were found in cluster TMB scores. We also found that immune-related pathways were enriched in C3.

Conclusion

LUAD subtypes based on immune signatures may aid in the development of novel treatment strategies for LUAD.

The Great Immune Escape: Understanding the Divergent Immune Response in Breast Cancer Subtypes

Breast cancer, the most common type of cancer affecting women, encompasses a collection of histologic (mainly ductal and lobular) and molecular subtypes exhibiting diverse clinical presentation, disease trajectories, treatment options, and outcomes. Immunotherapy has revolutionized treatment for some solid tumors but has shown limited promise for breast cancers. In this review, we summarize recent advances in our understanding of the complex interactions between tumor and immune cells in subtypes of breast cancer at the cellular and microenvironmental levels. We aim to provide a perspective on opportunities for future immunotherapy agents tailored to specific features of each subtype of breast cancer.

SIGNIFICANCE

Although there are currently over 200 ongoing clinical trials testing immunotherapeutics, such as immune-checkpoint blockade agents, these are largely restricted to the triple-negative and HER2+ subtypes and primarily focus on T cells. With the rapid expansion of new in vitro, in vivo, and clinical data, it is critical to identify and highlight the challenges and opportunities unique for each breast cancer subtype to drive the next generation of treatments that harness the immune system.

Immunotherapy for Triple-Negative Breast Cancer: Combination Strategies to Improve Outcome

Due to the absence of hormone receptor (both estrogen receptors and progesterone receptors) along with human epidermal growth factor receptor 2 (HER-2) amplification, the treatment of triple-negative breast cancer (TNBC) cannot benefit from endocrine or anti-HER-2 therapy. For a long time, chemotherapy was the only systemic treatment for TNBC. Due to the lack of effective treatment options, the prognosis for TNBC is extremely poor. The successful application of immune checkpoint inhibitors (ICIs) launched the era of immunotherapy in TNBC. However, the current findings show modest efficacy of programmed cell death- (ligand) 1 (PD-(L)1) inhibitors monotherapy and only a small proportion of patients can benefit from this approach. Based on the basic principles of immunotherapy and the characteristics of the tumor immune microenvironment (TIME) in TNBC, immune combination therapy is expected to further enhance the efficacy and expand the beneficiary population of patients. Given the diversity of drugs that can be combined, it is important to select effective biomarkers to identify the target population. Moreover, the side effects associated with the combination of multiple drugs should also be considered.

Use of Novel m6A Regulator-mediated Methylation Modification Patterns in Distinct Tumor Microenvironment Profiles to Identify and Predict Glioma Prognosis and Progression, T-cell Dysfunction, and Clinical Response to ICI Immunotherapy

BACKGROUND

The specific functions of RNA N6-methyladenosine (m6A) modifications in the glioma tumor microenvironment (TME) and glioma patient prognosis and treatment have not been determined to date.

OBJECTIVE

The objective of the study was to determine the role of m6A modifications in glioma TME.

METHODS

Nonnegative matrix factorization (NMF) methods were used to determine m6A clusters and m6A gene signatures based on 21 genes relating to m6A modifications. TME characteristics for each m6A cluster and m6A gene signature were quantified by established m6A score. The utility of m6A score was validated in immunotherapy and other antiangiogenic treatment cohorts.

RESULTS

Three m6A clusters were identified among 3,395 glioma samples, and they were linked to different biological activities and clinical outcomes. The m6A clusters were highly consistent with immune profiles known as immune-inflamed, immune-excluded, and immune-desert phenotypes. Clusters within individual tumors could predict glioma inflammation, molecular subtypes, TME stromal activity, genetic variation, alternative splicing, and prognosis. As for the m6A score and m6A gene signature, patients with low m6A scores exhibited an increased tumor mutation burden, immune activity, neoantigen load, and prolonged survival. A low m6A score indicated the potential for a low level of T-cell dysfunction, a considerably better treatment response, and durable clinical benefits from immunotherapy, bevacizumab and regorafenib.

CONCLUSION

Glioma m6A clusters and gene signatures have distinctive TME features. The m6A gene signature may guide prognostic assessments and promote the use of effective strategies.

The role of PRAME and NY-ESO-1 as potential therapeutic and prognostic biomarkers in triple-negative breast carcinomas

PRAME and NY-ESO-1 are cancer-testis antigens (CTAs) reported to be highly enriched in triple-negative breast cancers (TNBCs), against which vaccines and immunotherapies are currently being developed. This study aims to analyze PRAME and NY-ESO-1 expression in TNBCs and their correlation with clinical outcomes. This is a retrospective cohort study of TNBC patients who have undergone neoadjuvant chemotherapy. PRAME and NY-ESO-1 expression were assessed on pre-therapy biopsies as H-scores (percentage x intensity) with final H scores of 2-3 considered as positive. Association between expression and pathologic complete response (pCR), metastasis, and residual cancer burden (RCB) were assessed via logistic regression. Cox proportional hazards models were used to assess the association with progression-free survival. P-values < 0.05 were considered statistically significant. Sixty-three percent of 76 patients were positive for PRAME. In contrast, only 5 % were positive for NY-ESO-1. PRAME positivity was significantly associated with a lower likelihood of early metastatic disease (OR = 0.24, 95 % CI 0.08-0.62; P = 0.005). However, it was not significantly associated with pCR, RCB category, or progression-free survival. NY-ESO1 score was not significantly associated with early metastatic disease, pCR, RCB category, or progression-free survival. Our results suggest that PRAME positivity may be associated with a lower risk of early metastasis in TNBCs, but not with response to neoadjuvant chemotherapy or progression-free survival. The high expression of PRAME in TNBCs makes it a potential therapeutic target, while NY-ESO1 appears to be a less useful marker. However, further larger studies are needed to ascertain the utility of these markers.

Involvement of CHRNA6 in the Immune Response in Lung Squamous Cell Carcinoma and its Potential as a Drug Target for the Disease

BACKGROUND

Lung squamous cell carcinoma (LUSC) is a subtype of lung cancer with a poor prognosis and limited treatment options. Previous studies show that some components of the cholinergic pathway may play important roles in the tumorigenesis of lung cancer, including LUSC.

OBJECTIVE

The purpose of this study is to investigate the involvement of cholinergic genes in immune infiltration in LUSC, and identify the key genes in the pathway and analyze their potential as targets for LUSC treatment and novel drugs.

METHODS

We first screened the cholinergic genes associated with immune infiltration in LUSC based on transcriptomic samples and explored the correlation between the key genes and immune infiltrating cells and immune pathways. Then, we assessed the effect of immunotherapeutic response in the high and low-expression groups of key genes in vitro. And finally, we screened potential drugs for the treatment of LUSC.

RESULTS

We found that the expression of CHRNA6, the gene encoding the α6 subunit of nicotinic acetylcholine receptors (nAChR), was significantly correlated with the proportion of immune infiltrating cells in LUSC, and the high expression level of the gene was associated with poor prognosis of the disease. Also, the proportion of Tregs, M1 macrophages, and resting mast cells was correlated with the expression of CHRNA6. In addition, LUSC patients with higher CHRNA6 expression levels had better immunotherapy responses. Furthermore, we found that the drugs, i.e., adavosertib, varbulin and pyrazoloacridine, had a strong affinity with CHRNA6, with adavosertib binding most stably with the protein.

CONCLUSION

CHRNA6 may be associated with immune infiltration in LUSC and affects patient prognosis and immunotherapeutic response by regulating immune cells and immune pathways. In addition, adavosertib may be a potential drug for the treatment of LUSC.