Clinical significance of tumor-infiltrating lymphocytes in breast cancer

Identification and validation of a twelve immune infiltration-related lncRNA prognostic signature for bladder cancer

The prognosis of bladder cancer patients is strongly related to both the immune-infiltrating cells and the expression of lncRNAs. In this study, we analyzed the infiltration of immune cells in 403 bladder cancer samples obtained from TCGA by applying the ssGSEA to these samples, then dividing them into high/low immune cell infiltration groups. Based on these groupings, we found 404 differentially expressed immune infiltration-related lncRNAs, which were successively analyzed by univariate Cox regression, then Least Absolute Shrinkage and Selection Operator (LASSO), and finally stepwise multiple Cox regression. Then 12 differentially expressed immune infiltration-related lncRNAs were identified and used to construct a prognostic signature for bladder cancer. Subsequently, Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, and multivariate time-dependent ROC analyses (for 1, 3, 5 years) all revealed that this signature performed well in predicting overall survival and served as an independent prognostic factor for patients with bladder cancer. Finally, both TIMER and CIBESORT showed that this 12-lncRNA prognostic signature for bladder cancer was associated with the infiltration of immune cell subtypes. Besides, nomogram considered risk score and clinical characteristics was assembled and showed great performance. More importantly, we found our signature could well distinguish the drug response of patients with bladder cancer. High risk patients showed a better response to cisplatin, doxorubicin, and anti- CTLA4 immunotherapy, low risk patients showed a better response to methotrexate and anti-PD1 immunotherapy compared with each other.

Tumor-infiltrating exhausted CD8+ T cells dictate reduced survival in premenopausal estrogen receptor-positive breast cancer

CD8⁺ tumor-infiltrating lymphocytes (TILs) are associated with improved survival in triple-negative breast cancer (TNBC) yet have no association with survival in estrogen receptor–positive (ER⁺) BC. The basis for these contrasting findings remains elusive. We identified subsets of BC tumors infiltrated by CD8⁺ T cells with characteristic features of exhausted T cells (T_EX). Tumors with abundant CD8⁺ T_EX exhibited a distinct tumor microenvironment marked by amplified interferon-γ signaling–related pathways and higher programmed death ligand 1 expression. Paradoxically, higher levels of tumor-infiltrating CD8⁺ T_EX associated with decreased overall survival of patients with ER⁺ BC but not patients with TNBC. Moreover, high tumor expression of a CD8⁺ T_EX signature identified dramatically reduced survival in premenopausal, but not postmenopausal, patients with ER⁺ BC. Finally, we demonstrated the value of a tumor T_EX signature score in identifying high-risk premenopausal ER⁺ BC patients among those with intermediate Oncotype DX Breast Recurrence Scores. Our data highlight the complex relationship between CD8⁺ TILs, interferon-γ signaling, and ER status in BC patient survival. This work identifies tumor-infiltrating CD8⁺ T_EX as a key feature of reduced survival outcomes in premenopausal patients with early-stage ER⁺ BC.

Early-stage Triple-negative Breast Cancer: Time to Optimize Personalized Strategies

Triple-negative breast cancer (TNBC) accounts for approximately 15%-20% of breast cancers diagnosed worldwide, which amounts to almost 200 000 cases each year. Although historically TNBC is considered difficult to treat with a poor prognosis, there is emerging evidence showing excellent response rates in a subset of TNBC patients. Attempts to de-escalate chemotherapy in hormone-receptor-positive (HR+) and HER2-neu amplified breast cancer subtypes have been successful. At present, robust strategies to personalize therapy in early-stage TNBC do not exist, and despite excellent response rates in a subset of patients, all patients are exposed to the same several cycles of cytotoxic chemotherapy. Personalizing therapy in TNBC represents a challenge due to the scarcity of treatment options outside of cytotoxic chemotherapy and limited predictive and prognostic biomarkers to tailor treatment. Recent developments in understanding TNBC biology have sparked interest in exploring treatment optimization and personalization with the goal of achieving excellent response rates and long-term clinical outcomes, while simultaneously reducing physical, psychological, and financial toxicities for select patients. Here, we provide an update on the current evidence to support future studies examining de-escalating chemotherapy in patients with low-risk TNBC and adjuvant intensification strategies to improve outcomes for patients who are at high risk for systemic failure despite current standard-of-care treatments.

Identification and Characterization of Immunogene-Related Alternative Splicing Patterns and Tumor Microenvironment Infiltration Patterns in Breast Cancer

Alternative splicing (AS) plays a crucial role in tumor development and tumor microenvironment (TME) formation. However, our current knowledge about AS, especially immunogene-related alternative splicing (IGAS) patterns in cancers, remains limited. Herein, we identified and characterized post-transcriptional mechanisms of breast cancer based on IGAS, TME, prognosis, and immuno/chemotherapy. We screened the differentially spliced IGAS events and constructed the IGAS prognostic model (p-values < 0.001, AUC = 0.939), which could be used as an independent prognostic factor. Besides, the AS regulatory network suggested a complex cooperative or competitive relationship between splicing factors and IGAS events, which explained the diversity of splice isoforms. In addition, more than half of the immune cells displayed varying degrees of infiltration in the IGAS risk groups, and the prognostic characteristics of IGAS demonstrated a remarkable and consistent trend correlation with the infiltration levels of immune cell types. The IGAS risk groups showed substantial differences in the sensitivity of immunotherapy and chemotherapy. Finally, IGAS clusters defined by unsupervised cluster analysis had distinct prognostic patterns, suggesting an essential heterogeneity of IGAS events. Significant differences in immune infiltration and unique prognostic capacity of immune cells were also detected in each IGAS cluster. In conclusion, our comprehensive analysis remarkably enhanced the understanding of IGAS patterns and TME in breast cancer, which may help clarify the underlying mechanisms of IGAS in neoplasia and provide clues to molecular mechanisms of oncogenesis and progression.

A risk scoring system based on tumor microenvironment cells to predict prognosis and immune activity in triple-negative breast cancer

The tumor microenvironment (TME) interacting with the malignant cells plays a vital role in cancer development. Herein, we aim to establish and verify a scoring system based on the characteristics of TME cells for prognosis prediction and personalized treatment guidance in patients with triple-negative breast cancer (TNBC). 158 TNBC samples from The Cancer Genome Atlas (TCGA) were included as the training cohort, and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) (N = 297), as well as GSE58812 (N = 107), were included as the validation cohort. The enrichment scores of 64 immune and stromal cells were estimated by the xCell algorithm. In the training cohort, cells with prognostic significance were found out using univariate Cox regression analysis and further applied to the random survival forest (RSF) model. Based on the scores of M2 macrophages, CD8+ T cells, and CD4+ memory T cells, a risk scoring system was constructed, which divided TNBC patients into 4 phenotypes (M2low, M2highCD8+ThighCD4+Thigh, M2highCD8+ThighCD4+Tlow, and M2highCD8+Tlow). Furthermore, types 1 and 2 patients were merged into the low-risk group, while types 3 and 4 patients were in the high-risk group. The low-risk group had superior survival outcomes than the high-risk one, which was further confirmed in the validation cohort. Moreover, in the low-risk group, immune-related pathways were significantly enriched, and a higher level of antitumoral immune cells and immune checkpoint molecules, including PD-L1, PD-1, and CTLA-4, could be observed. Additionally, consistent results were achieved in the SYSUCC cohort when the scoring system was applied. In summary, this novel scoring system might predict the survival and immune activity of patients and might serve as a potential index for immunotherapy.

Extracellular Vesicles as Mediators of Therapy Resistance in the Breast Cancer Microenvironment

Resistance to various therapies, including novel immunotherapies, poses a major challenge in the management of breast cancer and is the leading cause of treatment failure. Bidirectional communication between breast cancer cells and the tumour microenvironment is now known to be an important contributor to therapy resistance. Several studies have demonstrated that crosstalk with the tumour microenvironment through extracellular vesicles is an important mechanism employed by cancer cells that leads to drug resistance via changes in protein, lipid and nucleic acid cargoes. Moreover, the cargo content enables extracellular vesicles to be used as effective biomarkers for predicting response to treatments and as potential therapeutic targets. This review summarises the literature to date regarding the role of extracellular vesicles in promoting therapy resistance in breast cancer through communication with the tumour microenvironment.

Characterized the diversity of ABCB1 subtypes in immunogenomic landscape for predicting the drug response in breast cancer

ABCB1 is an important gene that closely related to analgesic tolerance to opioids, and plays an important role in their postoperative treatment. Recent studies have demonstrated that ABCB1 genotype is significantly associated with the chemico-resistance and chemical sensitivity in breast cancer patients. So, it is become very important to investigate the important role of ABCB1 for predicting drug response in breast cancer patients. In this study, by conducting the Cox proportional hazards regression analysis in breast cancer patients, significant differences were found in prognosis between the ABCB1 high- and low-expression subtypes. Meanwhile, by using immune infiltration profiles as well as transcriptomics datasets, the ABCB1 high subtype was found to be significantly enriched in many immune-related KEGG pathways and biological processes, and was characterized by the high infiltration levels of immune cell types. Furthermore, bioinformatics inference revealed that the ABCB1 subtypes were associated with the therapeutic effect of immunotherapy, which would be important for patient prognosis. In conclusion, these findings may provide useful help for recognizing the diversity between ABCB1 subtypes in tumor immune microenvironment, and may unravel prognosis outcomes and immunotherapy utility for ABCB1 in breast cancer.

Prognostic Value of the Systemic Immune-Inflammation Index and Prognostic Nutritional Index in Patients With Medulloblastoma Undergoing Surgical Resection

Background: The progression and metastasis of cancers are associated with systematic immune inflammation and nutritional dysfunction. The systemic immune-inflammation index and prognostic nutritional index (PNI) have shown a prognostic impact in several malignancies. Therefore, our study aimed to evaluate immune inflammation and nutritional index prognostic significance in patients with medulloblastoma (MB).

Methods: We retrospectively analyzed 111 patients with MB between 2001 and 2021 at our institution. The optimal cutoff values for systemic immune-inflammation index (SII), neutrophil/lymphocyte ratio (NLR), monocyte/lymphocyte counts ration (MLR), and PNI were evaluated with receiver operating characteristic (ROC) curve analysis. Clinical characteristics and SII, NLR, MLR, and PNI were tested with the Pearson's chi-squared test. The Kaplan–Meier survival curves and the Cox proportional hazards model were used to evaluate the effects of immune inflammation and nutritional index on overall survival (OS).

Results: Receiver operating characteristic curve analysis determined the optimal SII, NLR, MLR, and PNI cutoff values of 2,278, 14.83, 0.219, and 56.5 that significantly interacts with OS and divided the patients into two groups. Comparative survival analysis exhibited that the high-SII cohort had significantly shorter OS (p = 0.0048) than the low-SII cohort. For the univariate analysis, the results revealed that preoperative hydrocephalus (p = 0.01), SII (p = 0.006), albumin–bilirubin score (ALBI) (p = 0.04), and coSII–PNI were predictors of OS. In the multivariate analysis, preoperative hydrocephalus (p < 0.001), ALBI (p = 0.010), SII (p < 0.001), and coSII–PNI as independent prognostic factors were significantly correlated with OS.

Conclusion: The preoperative SII, ALBI, and coSII–PNI serve as robust prognostic biomarkers for patients with MB undergoing surgical resection.

The Characteristics of Tumor Microenvironment in Triple Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a special subtype of breast cancer, accounting for 10-20% of breast cancers with high intrinsic heterogeneity. Its unique immune microenvironment, including high expression of vascular endothelial growth factors, tumor infiltrating lymphocytes (TILs), tumor-associated macrophages (TAMs), and other molecules that promote the growth and migration of tumor cells, has been shown to play a dual role in the occurrence, growth, and metastasis of TNBC. Understanding the TNBC microenvironment is of great significance for the prognosis and treatment of TNBC. In this article, we describe the composition and function of immune cells in the TNBC microenvironment and summarize the major cytokine growth factors and chemokines in the TNBC microenvironment. Finally, we discuss the progress of TNBC, cytokine-induced killer cell therapy, and immune checkpoint therapy.

Adoptive T-cell Immunotherapy: Perfecting Self-Defenses

As an important part of the immune system, T lymphocytes exhibit undoubtedly an important role in targeting and eradicating cancer. However, despite these characteristics, their natural antitumor response may be insufficient. Numerous clinical trials in terminally ill cancer patients testing the design of novel and efficient immunotherapeutic approaches based on the adoptive transfer of autologous tumor-specific T lymphocytes have shown encouraging results. Moreover, this also led to the approval of engineered T-cell therapies in patients. Herein, we will expand on the development and the use of such strategies using tumor-infiltrating lymphocytes or genetically engineered T-cells. We will also comment on the requirements and potential hurdles encountered when elaborating and implementing such treatments as well as the exciting prospects for this kind of emerging personalized medicine therapy.

Neoadjuvant pyrotinib plus trastuzumab and nab-paclitaxel for HER2-positive early or locally advanced breast cancer: an exploratory phase II trial

BACKGROUND

The anti-tumor activity and acceptable tolerability of pyrotinib plus chemotherapy have been demonstrated in phase III trials in human epidermal growth factor receptor 2-positive metastatic breast cancer (BC). In this study, we assessed the efficacy and safety of neoadjuvant pyrotinib plus trastuzumab and albumin-bound paclitaxel in women with human epidermal growth factor receptor 2-positive early or locally advanced BC.

METHODS

In this single-arm exploratory phase II trial, patients with untreated human epidermal growth factor receptor 2-positive BC (stage IIA-IIIC) received pyrotinib 400 mg once daily, trastuzumab 4 mg/kg loading dose, followed by 2 mg/kg once a week, and albumin-bound paclitaxel 125 mg/m2 once a week for four 21-day cycles before surgery. The primary endpoint of the study was total pathological complete response (pCR) rate, defined as no microscopic invasive tumor remnants in the breast and axillary lymph nodes. The secondary endpoints were investigator-assessed objective response rate (ORR) and adverse event profiles.

RESULTS

Between May 17, 2019 and November 26, 2019, a total of 21 patients were enrolled. The total pCR rate was 57.1% (12/21), whereas 23.8% (5/21) and 19.0% (4/21) of patients had minimal and moderate residual disease (RD), respectively. The ORR reached 100% (21/21) at the end of the neoadjuvant therapy. Grade ≥3 treatment-related adverse events were observed in 42.9% (9/21) of patients, including decreased neutrophil count [7 (33.3%)], diarrhoea [6 (28.6%)], decreased white blood cell count [5 (23.8%)], and vomiting [2 (9.5%)]. Adverse event-related dose reduction and interruption of pyrotinib occurred in 6 (28.6%) and 11 (52.4%) patients, respectively.

CONCLUSIONS

In women with human epidermal growth factor receptor 2-positive early or locally advanced BC, neoadjuvant pyrotinib plus trastuzumab and albumin-bound paclitaxel effectively promoted total pCR rate with an acceptable safety profile (ClinicalTrials.gov, NCT04152057).

Translational Advances in Cancer Prevention Agent Development (TACPAD) Virtual Workshop on Immunomodulatory Agents: Report

The National Cancer Institute (NCI) Division of Cancer Prevention (DCP) convened the "Translational Advances in Cancer Prevention Agent Development (TACPAD) Workshop on Immunomodulatory Agents" as a virtual 2-day workshop on September 13 to 14, 2021. The main goals of this workshop were to foster the exchange of ideas and potentially new collaborative interactions among leading cancer immunoprevention researchers from basic and clinical research and highlight new and emerging trends in immunoprevention. The workshop included an overview of the mechanistic classes of immunomodulatory agents and three sessions covering the gamut from preclinical to clinical studies. The workshop convened individuals working in immunology and cancer prevention to discuss trends in discovery and development of immunomodulatory agents individually and in combination with other chemopreventive agents or vaccines.

Futuristic approach to cancer treatment

Cancer is becoming one of the deadliest disease in both developed as well as developing countries and continuous effort is being made to find innovative therapies for myriad types of cancers that afflict the human body. Therapeutic options for cancer have grown exponentially over the time but we are quite a way off from finding a magic bullet that can help cure cancer and based on the current evidence we may never find a catch all cure ever and it becomes crucial that we keep on innovating and find multiple ways to attack the menace of this dreaded disease. Many patients suffer recurrence of disease and require second-line or in some cases more than two lines of treatment. In this review article we have discussed the available therapies along with the newer advancements that have been made in cancer therapy. Latest developments in treatment of various cancers that have been discussed include gene editing using CRISPR/Cas9, theranostics, viral mediated therapy, artificial intelligence, tumor infiltrating lymphocyte therapy, etc.

Integration of Genomic Profiling and Organoid Development in Precision Oncology

Precision oncology involves an innovative personalized treatment strategy for each cancer patient that provides strategies and options for cancer treatment. Currently, personalized cancer medicine is primarily based on molecular matching. Next-generation sequencing and related technologies, such as single-cell whole-transcriptome sequencing, enable the accurate elucidation of the genetic landscape in individual cancer patients and consequently provide clinical benefits. Furthermore, advances in cancer organoid models that represent genetic variations and mutations in individual cancer patients have direct and important clinical implications in precision oncology. This review aimed to discuss recent advances, clinical potential, and limitations of genomic profiling and the use of organoids in breast and ovarian cancer. We also discuss the integration of genomic profiling and organoid models for applications in cancer precision medicine.

Therapeutic Potential of Thymoquinone in Triple-Negative Breast Cancer Prevention and Progression through the Modulation of the Tumor Microenvironment

To date, the tumor microenvironment (TME) has gained considerable attention in various areas of cancer research due to its role in driving a loss of immune surveillance and enabling rapid advanced tumor development and progression. The TME plays an integral role in driving advanced aggressive breast cancers, including triple-negative breast cancer (TNBC), a pivotal mediator for tumor cells to communicate with the surrounding cells via lymphatic and circulatory systems. Furthermore, the TME plays a significant role in all steps and stages of carcinogenesis by promoting and stimulating uncontrolled cell proliferation and protecting tumor cells from the immune system. Various cellular components of the TME work together to drive cancer processes, some of which include tumor-associated adipocytes, fibroblasts, macrophages, and neutrophils which sustain perpetual amplification and release of pro-inflammatory molecules such as cytokines. Thymoquinone (TQ), a natural chemical component from black cumin seed, is widely used traditionally and now in clinical trials for the treatment/prevention of multiple types of cancer, showing a potential to mitigate components of TME at various stages by various pathways. In this review, we focus on the role of TME in TNBC cancer progression and the effect of TQ on the TME, emphasizing their anticipated role in the prevention and treatment of TNBC. It was concluded from this review that the multiple components of the TME serve as a critical part of TNBC tumor promotion and stimulation of uncontrolled cell proliferation. Meanwhile, TQ could be a crucial compound in the prevention and progression of TNBC therapy through the modulation of the TME.

CREM Is Correlated With Immune-Suppressive Microenvironment and Predicts Poor Prognosis in Gastric Adenocarcinoma

The transcriptional repressor cAMP response element modulator (CREM) has an important role in T-cell development. In this study, we used the integrated Bioinformatics Methods to explore the role of CREM in gastric adenocarcinoma (GAC). Our results showed that high CREM expression was closely related with poorer overall survival in GAC. By GSEA cluster analysis, we found that the high expression of CREM was associated with the cancer-associated pathway in GAC. Moreover, single-cell sequencing data showed that CREM is mainly localized in exhausted CD8⁺ T cells. Its prognostic value and the potential function lead to T-cell exhaustion in the tumor microenvironment (TME). Similar results were also obtained in glioma and lung cancer. High expression of CREM, correlated with clinical relevance of GAC, was associated with T-cell exhaustion and M2 polarization in GAC. These findings suggest that CREM can be used as a prognostic biomarker in GAC, which might provide a novel direction to explore the pathogenesis of GAC.

Systemic Immune-Inflammation Index Is a Prognostic Factor for Breast Cancer Patients After Curative Resection

Background

The preoperative systemic immune-inflammation index (SII) is correlated with prognosis in several malignancies. The aim of this study was to investigate the prognosis value of SII in patients with resected breast cancer.

Materials and Methods

A total of 784 breast cancer patients who underwent surgical resection were consecutively investigated. The optimal cutoff value of SII was evaluated using the receiver operating characteristic (ROC) curve. The collection of SII with clinicopathological characteristic and prognosis was further evaluated.

Results

The optimal cutoff value for SII in the prediction of survival was 514 according to ROC curve analysis. A high SII was significantly correlated with younger age (P = 0.037), PR status (P < 0.001), and HER2 status (P = 0.035). Univariate analysis revealed that SII (P < 0.001), T-stage (P < 0.001), lymph node involvement post-surgery (P = 0.024), and histological grade (P < 0.001) were significantly related to DFS, and SII (P < 0.001), T-stage (P = 0.003), lymph node involvement post-surgery (P = 0.006), and histological grade (P < 0.001) were significantly associated with OS. In multivariate analysis, a high SII was an independent worse prognostic factor for DFS (HR, 4.530; 95% CI, 3.279-6.258; P < 0.001) and OS (HR, 3.825; 95% CI, 2.594-5.640; P < 0.001) in all the enrolled patients. Furthermore, subgroup analysis of molecular subtype revealed that SII was significantly associated with prognosis in all subtypes.

Conclusion

Preoperative SII is a simple and useful prognostic factor for predicting long-term outcomes for breast cancer patients undergoing surgery.

The role of estrogen receptor signaling in suppressing the immune response to cancer

Immune checkpoint blockade (ICB) therapies are standard of care for the treatment of many solid tumors. While some patients with cancer experience exceptional and long-term responses, intrinsic and acquired mechanisms of resistance limit the clinical efficacy of ICBs. In addition, ICBs can elicit life-threatening side effects. Alternative options that can increase ICB responses without added toxicities are needed. In this issue of the JCI, Chakraborty et al. explored the role of estrogen receptor α (ERα) in modulating ICB activity. Using transcriptomics and preclinical melanoma models, the authors show that ERα signaling in tumor-associated macrophages contributed to an immune-suppressive state within the tumor microenvironment (TME) by promoting CD8+ T cell dysfunction and exhaustion. Further, in murine melanoma models, the addition of fulvestrant, a selective estrogen receptor downregulator (SERD) approved for the treatment of breast cancer, enhanced the antitumor effects of ICB. These results provide a rationale for human trials to test the combination of antiestrogens with ICBs.

Biomimetic nanoparticles deliver mRNAs encoding costimulatory receptors and enhance T cell mediated cancer immunotherapy

Antibodies targeting costimulatory receptors of T cells have been developed for the activation of T cell immunity in cancer immunotherapy. However, costimulatory molecule expression is often lacking in tumor-infiltrating immune cells, which can impede antibody-mediated immunotherapy. Here, we hypothesize that delivery of costimulatory receptor mRNA to tumor-infiltrating T cells will enhance the antitumor effects of antibodies. We first design a library of biomimetic nanoparticles and find that phospholipid nanoparticles (PL1) effectively deliver costimulatory receptor mRNA (CD137 or OX40) to T cells. Then, we demonstrate that the combination of PL1-OX40 mRNA and anti-OX40 antibody exhibits significantly improved antitumor activity compared to anti-OX40 antibody alone in multiple tumor models. This treatment regimen results in a 60% complete response rate in the A20 tumor model, with these mice being resistant to rechallenge by A20 tumor cells. Additionally, the combination of PL1-OX40 mRNA and anti-OX40 antibody significantly boosts the antitumor immune response to anti-PD-1 + anti-CTLA-4 antibodies in the B16F10 tumor model. This study supports the concept of delivering mRNA encoding costimulatory receptors in combination with the corresponding agonistic antibody as a strategy to enhance cancer immunotherapy.

The Leptin Axis and Its Association With the Adaptive Immune System in Breast Cancer

Adipose tissue secretes various peptides, including leptin. This hormone acts through the leptin receptor (Ob-R), which is expressed ubiquitously on the surface of various cells, including breast cancer cells and immune cells. Increasing evidence points to an interaction between the tumor microenvironment, tumor cells, and the immune system. Leptin plays an important role in breast cancer tumorigenesis and may be implicated in activation of the immune system. While breast cancer cannot be considered an immunogenic cancer, the triple-negative subtype is an exception. Specific immune cells - tumor infiltrating lymphocytes - are involved in the immune response and act as predictive and prognostic factors in certain breast cancer subtypes. The aim of this article is to review the interaction between adipose tissue, through the expression of leptin and its receptor, and the adaptive immune system in breast cancer.

Intratumoral Heterogeneity and Immune Response Indicators to Predict Overall Survival in a Retrospective Study of HER2-Borderline (IHC 2+) Breast Cancer Patients

Breast cancer (BC) categorized as human epidermal growth factor receptor 2 (HER2) borderline [2+ by immunohistochemistry (IHC 2+)] presents challenges for the testing, frequently obscured by intratumoral heterogeneity (ITH). This leads to difficulties in therapy decisions. We aimed to establish prognostic models of overall survival (OS) of these patients, which take into account spatial aspects of ITH and tumor microenvironment by using hexagonal tiling analytics of digital image analysis (DIA). In particular, we assessed the prognostic value of Immunogradient indicators at the tumor–stroma interface zone (IZ) as a feature of antitumor immune response. Surgical excision samples stained for estrogen receptor (ER), progesterone receptor (PR), Ki67, HER2, and CD8 from 275 patients with HER2 IHC 2+ invasive ductal BC were used in the study. DIA outputs were subsampled by HexT for ITH quantification and tumor microenvironment extraction for Immunogradient indicators. Multiple Cox regression revealed HER2 membrane completeness (HER2 MC) (HR: 0.18, p = 0.0007), its spatial entropy (HR: 0.37, p = 0.0341), and ER contrast (HR: 0.21, p = 0.0449) as independent predictors of better OS, with worse OS predicted by pT status (HR: 6.04, p = 0.0014) in the HER2 non-amplified patients. In the HER2-amplified patients, HER2 MC contrast (HR: 0.35, p = 0.0367) and CEP17 copy number (HR: 0.19, p = 0.0035) were independent predictors of better OS along with worse OS predicted by pN status (HR: 4.75, p = 0.0018). In the non-amplified tumors, three Immunogradient indicators provided the independent prognostic value: CD8 density in the tumor aspect of the IZ and CD8 center of mass were associated with better OS (HR: 0.23, p = 0.0079 and 0.14, p = 0.0014, respectively), and CD8 density variance along the tumor edge predicted worse OS (HR: 9.45, p = 0.0002). Combining these three computational indicators of the CD8 cell spatial distribution within the tumor microenvironment augmented prognostic stratification of the patients. In the HER2-amplified group, CD8 cell density in the tumor aspect of the IZ was the only independent immune response feature to predict better OS (HR: 0.22, p = 0.0047). In conclusion, we present novel prognostic models, based on computational ITH and Immunogradient indicators of the IHC biomarkers, in HER2 IHC 2+ BC patients.

Smart exosomes with lymph node homing and immune-amplifying capacities for enhanced immunotherapy of metastatic breast cancer

Tumor-draining lymph nodes (TDLNs) are the primary sites to initiate immune responses against cancer, as well as the origin of metastasis for most breast cancer cases. Reverting the immunosuppression microenvironment in TDLNs is critical to improving the outcome of the malignancy, though still a big technical challenge. In this study, a type of smart exosomes was developed in which the exosome surface was functionally engineered with CD62L (L-selectin, a gene for lymphocyte homing to lymph nodes) and OX40L (CD134L, a gene for effector T cell expansion and regulatory T cell [Treg] inhibition) by forced expression of the genes in the donor cells. Compared with control exosomes, the smart exosomes displayed strong TDLN homing capacity in the 4T1 syngeneic mouse model. Moreover, injection of the smart exosomes activated effector T cells and inhibited Treg induction, thereby amplifying the antitumor immune response and inhibiting tumor development. Together, the engineered smart exosomes provide a novel nanoplatform for TDLN-targeted delivery and cancer immunotherapy.

Low Expression of PLAT in Breast Cancer Infers Poor Prognosis and High Immune Infiltrating Level

Purpose

Breast cancer accounts for the highest incidence of tumors in women. Immune infiltrating of the tumor microenvironment positively correlates with the overall survival of breast cancer patients. PLAT can affect the development of many cancers, but its mechanism in breast cancer is unclear. We assessed the correlation between PLAT and immune infiltrating in breast cancer based on the TCGA database.

Patients and Methods

The expression and DNA methylation of PLAT in breast cancer with different clinical characteristics was tested by Wilcoxon signed rank test and displayed by box plot. Sequentially, Kaplan–Meier plot was employed to compare the difference in overall survival rates between patients with different expressed levels. Univariate and multivariate Cox regression analyses were used to validate whether PLAT is an independent prognostic factor of breast cancer. After that, GO, KEGG, and gene-set enrichment analysis were employed to do functional enrichment analysis. Finally, TIMER, TISIDB database, and ssGSEA algorithm were used to assess the correlation between PLAT expression and various immune characteristics. The correlation between PLAT expression and DNA methylation was examined by Pearson correlation coefficient.

Results

PLAT displays differential expression levels in breast cancer patients with various clinical characteristics. As an independent protective factor for breast cancer, PLAT may significantly correlate with the immune status of breast cancer by adjusting many immune molecules and affecting the immune infiltration in the tumor microenvironment. DNA methylation of PLAT downregulates the gene expression and affects the prognosis of breast cancer.

Conclusion

PLAT can be considered a potential biomarker to predict breast cancer prognosis and might contribute to the development of immunological treatment strategies.

A combination strategy based on an Au nanorod/doxorubicin gel via mild photothermal therapy combined with antigen-capturing liposomes and anti-PD-L1 agent promote a positive shift in the cancer-immunity cycle

The antitumor immune response involves a cascade of cancer-immunity cycles. Developing a combination therapy aimed at the cancer-immunity cycle is of great importance. In this research, we designed and tested a combined therapeutic-Au nanorod (AuNR)/doxorubicin (DOX) gel (AuNR/DOX gel)-in which the sustained release of DOX was controlled by Pluronic gel. DOX served as an immunogenic tumor cell death (ICD) inducer, triggering the production of damage-associated molecular patterns (DAMPs). Mild photothermal therapy (Mild PTT) produced by 880 nm laser-irradiated AuNRs also generated tumor-associated antigens. Maleimide-modified liposomes (L-Mals), as antigen capturing agents, promoted tumor antigen uptake by DCs. Ultimately, more CD8+ T cells and fewer regulatory T cells (Tregs) infiltrated the tumor, eliciting antitumor responses from the PD-L1 antibody. Our results indicate that this combination strategy promotes a positive shift in the cancer-immunity cycle and holds much promise for combination strategy will lead to development of an antitumor drug delivery system. STATEMENT OF SIGNIFICANCE: Developing a combination therapy for cancer-immunity cycle is of great importance due to antitumor immune response involving a cascade of cancer-immunity cycles. Cancer-immunity cycle usually includes tumor antigen release, antigen presentation, immune activation, trafficking, infiltration, specific recognition of tumor cells by T cells, and finally cancer cell killing. In this research, we designed a combination strategy based on Au nanorod/doxorubicin gel via mild photothermal therapy combined with antigen-capturing liposomes and anti-PD-L1 agent promoting a positive shift in the cancer-immunity cycle. Our results indicate that this combination strategy promotes a positive shift in the cancer-immunity cycle and holds much promise for combination strategy will lead to development of an antitumor drug delivery system.

Expression and Clinical Significance of Origin Recognition Complex Subunit 6 in Breast Cancer – A Comprehensive Bioinformatics Analysis

Objective

We aimed to investigate the expression, diagnostic and prognostic values, and potential molecular mechanisms of the origin recognition complex (ORC) in breast cancer (BC).

Methods

Kaplan–Meier estimation was used to assess the prognostic value of ORC genes, and Oncomine, TCGA, GEO and ULCAN databases were used to analyze their expression in BC. Wilcoxon rank-sum tests were used to evaluate the relationship between ORC gene expression levels and BC clinicopathological features. Receiver operating characteristic (ROC) curves were used to assess the diagnostic value of ORC genes in BC. Survival analysis was performed using Kaplan–Meier estimation and Cox regression. A nomogram was constructed to predict 1-, 3-, and 5-year survival probabilities in BC. Gene set enrichment analysis (GSEA) and immune infiltration were used to investigate potential molecular mechanisms of the ORC.

Results

ORC1L and ORC6L were highly expressed in BC compared with healthy tissue, while ORC5L expression patterns were inconsistent; no significant differences in ORC2L, ORC3L or ORC4L expression were observed between BC and healthy tissues. ORC1L and ORC6L expression levels were significantly correlated with age, tumor (T) stage and molecular subtype; ORC5L expression was significantly correlated with age and number of nearby lymph nodes with cancer (N stage). ORC6L expression had the highest diagnostic value in BC and was an independent prognostic factor for poor overall survival (OS). ORC6L may be involved in cell cycle progression and may regulate cancer signaling pathways, including NF-κB, P53, and WNT, in BC. ORC6L expression was also associated with immune infiltration.

Conclusion

ORC1L and ORC6L are highly expressed in BC; ORC6L has a high diagnostic value and is an independent prognostic factor for poor OS. ORC6L may be involved in the initiation and progression of BC by regulating cell cycle progression, promoting cancer signaling pathway activation, and influencing tumor immune cell infiltration.

The Immune Landscape of Breast Cancer: Strategies for Overcoming Immunotherapy Resistance

Simple Summary

Immunotherapy is a rapidly advancing field in breast cancer treatment, however, it encounters many obstacles that leave open gateways for breast cancer cells to resist novel immunotherapies. It is believed that the tumor microenvironment consisting of cancer, stromal, and immune cells as well as a plethora of tumor-promoting soluble factors, is responsible for the failure of therapeutic strategies in cancer, including breast tumors. Therefore, an in-depth understanding of key barriers to effective immunotherapy, focusing the research efforts on harnessing the power of the immune system, and thus, developing new strategies to overcome the resistance may contribute significantly to increase breast cancer patient survival. In this review, we discuss the latest reports regarding the strategies rendering the immunosuppressive tumor microenvironment more sensitive to immunotherapy in breast cancers, HER2-positive and triple-negative types of breast cancer, which are attractive from an immunotherapeutic point of view.

Abstract

Breast cancer (BC) has traditionally been considered to be not inherently immunogenic and insufficiently represented by immune cell infiltrates. Therefore, for a long time, it was thought that the immunotherapies targeting this type of cancer and its microenvironment were not justified and would not bring benefits for breast cancer patients. Nevertheless, to date, a considerable number of reports have indicated tumor-infiltrating lymphocytes (TILs) as a prognostic and clinically relevant biomarker in breast cancer. A high TILs expression has been demonstrated in primary tumors, of both, HER2-positive BC and triple-negative (TNBC), of patients before treatment, as well as after treatment with adjuvant and neoadjuvant chemotherapy. Another milestone was reached in advanced TNBC immunotherapy with the help of the immune checkpoint inhibitors directed against the PD-L1 molecule. Although those findings, together with the recent developments in chimeric antigen receptor T cell therapies, show immense promise for significant advancements in breast cancer treatments, there are still various obstacles to the optimal activity of immunotherapeutics in BC treatment. Of these, the immunosuppressive tumor microenvironment constitutes a key barrier that greatly hinders the success of immunotherapies in the most aggressive types of breast cancer, HER2-positive and TNBC. Therefore, the improvement of the current and the demand for the development of new immunotherapeutic strategies is strongly warranted.

Autophagy: A promising target for triple negative breast cancers

Triple negative breast cancer (TNBC) is the most aggressive type of breast cancers which constitutes about 15% of all breast cancer cases and characterized by negative expression of hormonal receptors and human epidermal growth factor receptor 2 (HER2). Thus, endocrine and HER2 targeted therapies are not effective toward TNBCs, and they mainly rely on chemotherapy and surgery for treatment. Despite recent advances in chemotherapy, 40% of TNBC patients develop a metastatic relapse and recurrence. Therefore, understanding the molecular profile of TNBC is warranted to identify targets that can be selected for the development of a new and effective therapeutic approach. Autophagy is an internal defensive mechanism that allows the cells to survive under different stressors. It has been well known that autophagy exerts a crucial role in cancer progression. The critical role of autophagy in TNBC progression is emerging in recent years. This review will discuss autophagic pathway, how autophagy affects TNBC progression and recent therapeutic approaches that can target autophagy as a new treatment modality.

Systematic Analysis Uncovers Associations of PGK1 with Prognosis and Immunological Characteristics in Breast Cancer

Objective

Phosphoglycerate kinase 1 (PGK1) is an essential enzyme in the process of glycolysis and mitochondrial metabolism. Herein, we conducted a systematic analysis to uncover the clinical implication of PGK1 deregulation in breast cancer.

Methods

Expression pattern and prognostic significance of PGK1 were comprehensively assessed across pan-cancer based on RNA-seq profiles from the TCGA project. Associations of PGK1 with immunological features in the tumor microenvironment (immune checkpoints, immune response predictors (tumor mutation burden (TMB) and microsatellite instability (MSI)), and tumor-infiltrating immune cells) were systematically analyzed. The role of PGK1 in the prediction of breast cancer prognosis was also evaluated. GSEA was presented for investigating biological pathways involved in PGK1.

Results

PGK1 was specifically overexpressed in most of cancer types, including breast cancer. High PGK1 expression was indicative of undesirable overall survival, progression-free interval, disease-specific survival, and disease-free interval for various cancers. Furthermore, high PGK1 levels exhibited prominent correlations to immune checkpoints and high response to immunotherapy across pan-cancer. Notably, ROC curves confirmed that PGK1 can robustly predict breast cancer prognosis. Furthermore, PGK1 might shape an inflamed tumor microenvironment following the evidence that PGK1 was positively correlated to the abundance levels of tumor-infiltrating immune cells such as CD8+ T cell and NK cell in breast cancer. GSEA results revealed that PGK1 participated in metabolism and carcinogenic pathways.

Conclusion

Collectively, PGK1 was capable of robustly predicting the prognosis and response to cancer immunotherapy in breast cancer.

The Impact of Immune Microenvironment on the Prognosis of Pancreatic Ductal Adenocarcinoma Based on Multi-Omics Analysis

Pancreatic ductal adenocarcinoma (PDAC) is a malignant tumor characterized by rapid progression, early metastasis, high recurrence, and limited responsiveness to conventional therapies. The 5-year survival rate of PDAC is extremely low (<8%), which lacks effective prognostic evaluation indicators. In this study, we used xCell to analyze infiltrating immune cells in a tumor and through the univariate and multivariate Cox analyses screened out two prognosis-related immune cells, CD4⁺T_N and common lymphoid progenitor (CLP), which were used to construct a Cox model and figure out the risk-score. It was found that the constructed model could greatly improve the sensitivity of prognostic evaluation, that the higher the risk-score, the worse the prognosis. In addition, the risk-score could also identify molecular subtypes with poor prognosis and immunotherapy sensitivity. Through transcriptome and whole-exome sequencing analysis of PDAC dataset from The Cancer Genome Atlas (TCGA), it was found that copy number deletion and low expression of CCL19 might be crucial factors to affect the risk-score. Lastly, validation of the above findings was confirmed not only in Gene Expression Omnibus (GEO) datasets but also in our PDAC patient samples, Peking2020 cohort.

Estrogen receptor-positive breast cancer survival prediction and analysis of resistance-related genes introduction

Background

In recent years, ER+ and HER2- breast cancer of adjuvant therapy has made great progress, including chemotherapy and endocrine therapy. We found that the responsiveness of breast cancer treatment was related to the prognosis of patients. However, reliable prognostic signatures based on ER+ and HER2- breast cancer and drug resistance-related prognostic markers have not been well confirmed, This study in amied to establish a drug resistance-related gene signature for risk stratification in ER+ and HER2- breast cancer.

Methods

We used the data from The Cancer Genoma Atlas (TCGA) breast cancer dataset and gene expression database (Gene Expression Omnibus, GEO), constructed a risk profile based on four drug resistance-related genes, and developed a nomogram to predict the survival of patients with I-III ER+ and HER2- breast cancer. At the same time, we analyzed the relationship between immune infiltration and the expression of these four genes or risk groups.

Results

Four drug resistance genes (AMIGO2, LGALS3BP, SCUBE2 and WLS) were found to be promising tools for ER+ and HER2- breast cancer risk stratification. Then, the nomogram, which combines genetic characteristics with known risk factors, produced better performance and net benefits in calibration and decision curve analysis. Similar results were validated in three separate GEO cohorts. All of these results showed that the model can be used as a prognostic classifier for clinical decision-making, individual prediction and treatment, as well as follow-up.

Exploration of a Novel Prognostic Risk Signature and Its Effect on the Immune Response in Nasopharyngeal Carcinoma

Nasopharyngeal carcinoma (NPC) is a highly invasive and metastatic carcinoma with different molecular characteristics and clinical outcomes. In this work, we aimed to establish a novel gene signature that could predict the prognosis of NPC patients. A total of 13 significant genes between the recurrence/metastasis (RM) group and the no recurrence/metastasis (no-RM) group were identified by machine learning from RNA-Seq data including 60 NPC tumor biopsies. Based on these genes, a 4-mRNA signature (considering U2AF1L5, TMEM265, GLB1L and MLF1) was identified. Receiver operating characteristic (ROC) and Kaplan-Meier (K-M) analyses indicated that this signature had good prognostic value for NPC. The overall survival (OS) and progression-free survival (PFS) of the patients in the high-risk group were significantly shorter than those of the patients in the low-risk group (p = 0.00126 and p = 0.000059, respectively). The area under the ROC curve (AUC) values of the 4-mRNA signature were higher than those of T stage and N stage for OS (0.893 vs 0.619 and 0.582, respectively) and PFS (0.86 vs 0.538 and 0.622, respectively). Furthermore, the 4-mRNA signature was closely associated with cell proliferation and the immune response. The expression of GLB1L and TMEM265 was associated with the level of tumor-infiltrating immune cells (r > 0.4, p < 0.05). We have validated the model through measuring the expression levels of the 4-mRNA signature by qRT-PCR, in an independent cohort of NPC patients. Here, we report a novel gene signature that can serve as a new tool for predicting the prognosis of NPC patients.

Lysophosphatidic Acid Receptor 6 (LPAR6) Is a Potential Biomarker Associated with Lung Adenocarcinoma

LPAR6 is the most recently determined G-protein-coupled receptor of the lysophosphatidic acid receptor, and very few of studies have demonstrated the performance of LPAR6 in cancers. Moreover, the relationship of LPAR6 to the potential of prognosis and tumor infiltration immune cells in different types of cancer are still unclarified. In this study, the mRNA expression of LPAR6 and its clinical characteristics were evaluated on various databases. The association between LPAR6 and immune infiltrates of various types of cancer were investigated via TIMER. Immunohistochemistry (IHC) for LPAR6 in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) tissue microarray with patients’ information was detected. We constructed a systematic prognostic landscape in a variety of types of cancer base on the expression level of mRNA. We enclosed that higher LPAR6 mRNA expression level was associated with better overall survival in some types of malignancy. Moreover, LPAR6 significantly affects the prognostic potential of various cancers in The Cancer Genome Atlas Program (TCGA), especially in lung cancer. Tissue microarrays of lung cancer patient cohorts demonstrated that a higher protein level of LPAR6 was correlated to better overall survival of LUAD rather than LUSC cohorts. Further research indicated that the underlying mechanism of this phenome might be the mRNA expression level of LPAR6 was positively associated to infiltrating statuses of devious immunocytes in LUAD rather than in LUSC, that is, LPAR6 expression potentially contributes to the activation and recruiting of T cells (CD8+ T, naive T, effector T cell) and NK cells and inactivates Tregs, decreases T cell exhaustion and regulates T-helper (Th) cells in LUAD. Our discovery implies that LPAR6 is associated with prognostic potential and immune-infiltrating levels in LUAD. These discoveries imply that LPAR6 could be a promising novel biomarker for indicating the prognosis potential of LUAD patients.

Identification of a risk prediction model for clinical prognosis in HER2 positive breast cancer patients

Background New biomarkers are needed to identify different clinical outcomes for HER2+ breast cancer (BC). Methods Differential genes of HER2+ BC were screened based on TCGA database. We used WGCNA to identify the genes related to the survival. Genetic Algorithm was used to structure risk prediction model. The prognostic model was validated in GSE data. Results We constructed a risk prediction model of 6 genes to identify prognosis of HER2+ BC, including CLEC9A, PLD4, PIM1, PTK2B, AKNAD1 and C15orf27. Kaplan-Meier curve showed that the model effectively distinguished the survival of HER2+ BC patients. The multivariate Cox regression suggested that the risk model was an independent predictor for HER2+ BC. Analysis related to immune showed that significant differences in immune infiltration between high- and low-risk groups classified by the prognostic model. Conclusions Our study identified a risk prediction model of 6 genes that could distinguish the prognosis of HER2+ BC.

Comprehensive Analysis of Pyroptosis-Related Genes and Tumor Microenvironment Infiltration Characterization in Breast Cancer

Background

Immunotherapy has emerged as a significant strategy to treat numerous tumors. The positive response to immunotherapy depends on the dynamic interaction between tumor cells and infiltrating lymphocytes in the tumor microenvironment (TME). Pyroptosis, inflammation-induced cell death, is intricately associated with several tumors. However, the relationship between pyroptosis and clinical prognosis, immune cell infiltration, and immunotherapy effect is unclear in breast cancer (BRCA).

Methods

We comprehensively evaluated 33 pyroptosis-related genes and systematically assessed the relationship between pyroptosis and tumor progression, prognosis, and immune cell infiltration. The PyroptosisScore was used to quantify the pyroptosis pattern of a single tumor patient. We then assessed their values for predicting prognoses and therapeutic responses in BRCA.

Results

Three different modes of PyroptosisClusters were determined. The characteristics of TME cell infiltration in these three PyroptosisClusters were highly consistent with three immunophenotypes of tumors, including immune-excluded, immune-inflamed, and immune-desert phenotypes. Comprehensive bioinformatics analysis revealed that patients with a low PyroptosisScore had higher immune checkpoint expression, higher immune checkpoint inhibitor (ICI) scores, increased immune microenvironment infiltration, and were more sensitive to immunotherapy than those with a high PyroptosisScore.

Conclusions

Our findings revealed the crucial role of pyroptosis in maintaining the diversity and complexity of TME. Pyroptosis is closely related to tumor progression, tumor prognosis, and immunotherapy response. Evaluating the PyroptosisScore of a single tumor can assist in understanding the characteristics of TME infiltration and lead to the development of more effective immunotherapy strategies.

Updated efficacy of adjuvant epirubicin plus cyclophosphamide followed by taxanes versus carboplatin plus taxanes in early triple-negative breast cancer in phase 2 trial: 8.1-year median follow-up

BACKGROUND

Paclitaxel/docetaxel after doxorubicin plus cyclophosphamide (ECT) is considered as an adjuvant chemotherapy and improves the survival of early triple-negative breast cancer (TNBC) patients. We aim to assess whether carboplatin plus taxanes (TP) is non-inferior to ECT in prolonging the survival time.

METHODS

TNBC patients were randomized (1:1) to receive ECT (90 mg/m² epirubicin + 600 mg/m² cyclophosphamide followed by 75 mg/m² docetaxel or 175 mg/m² paclitaxel every 3 weeks, n = 154) or TP (75 mg/m² docetaxel or 175 mg/m² paclitaxel + carboplatin AUC 5 every 3 weeks, n = 154). These expression of SPARC, PD-L1, and BRCA were studied. Patients were followed up for disease-free survival (DFS), overall survival (OS), and safety.

RESULTS

We recruited 308 TNBC patients (median follow-up of 97.6 months). The median DFS and OS were not reached; the 8-year DFS rate of ECT and TP arms was 78.4% and 81.7%, respectively, while the 8-year OS rate were 87.2% and 89.1%, respectively. In the SPARC (> 50%) subgroup analysis, the TP arm had longer DFS (P = 0.049) and a tendency with better OS (P = 0.06) than ECT arm. No significant differences were observed in the DFS and OS between the ECT arm and TP arm in TNBC with SPARC (≤ 50%), PD-L1 (-) PD-L1 (+), and BRCA mutation or BRCA wild (all P values > 0.05).

CONCLUSION

TP showed non-inferiority for DFS and OS compared with ECT in early TNBC. TP may be an effective alternative chemotherapy for TNBC patients whom the standard ECT regimen is not being used.

TRAIL REGISTRATION

ClinicalTrials.gov identifier NCT01150513.

Impact of Epithelial-Mesenchymal Transition on the Immune Landscape in Breast Cancer

The impact of epithelial-mesenchymal transition (EMT) signature on the immune infiltrate present in the breast cancer tumor microenvironment (TME) is still poorly understood. Since there is mounting interest in the use of immunotherapy for the treatment of subsets of breast cancer patients, it is of major importance to understand the fundamental tumor characteristics which dictate the inter-tumor heterogeneity in immune landscapes. We aimed to assess the impact of EMT-related markers on the nature and magnitude of the inflammatory infiltrate present in breast cancer TME and their association with the clinicopathological parameters. Tissue microarrays were constructed from 144 formalin-fixed paraffin-embedded invasive breast cancer tumor samples. The protein expression patterns of Snail, Twist, ZEB1, N-cadherin, Vimentin, GRHL2, E-cadherin, and EpCAM were examined by immunohistochemistry (IHC). The inflammatory infiltrate in the TME was assessed semi-quantitatively on hematoxylin and eosin (H&E)-stained whole sections and was characterized using IHC. The inflammatory infiltrate was more intense in poorly differentiated carcinomas and triple-negative carcinomas in which the expression of E-cadherin and GRHL2 was reduced, while EpCAM was overexpressed. Most EMT-related markers correlated with plasma cell infiltration of the TME. Taken together, our findings reveal that the EMT signature might impact the immune response in the TME.

Helicobacter pylori in gastric cancer: Features of infection and their correlations with long-term results of treatment

BACKGROUND

Helicobacter pylori (H. pylori) is a spiral-shaped bacterium responsible for the development of chronic gastritis, gastric ulcer, gastric cancer (GC), and MALT-lymphoma of the stomach. H. pylori can be present in the gastric mucosa (GM) in both spiral and coccoid forms. However, it is not known whether the severity of GM contamination by various vegetative forms of H. pylori is associated with clinical and morphological characteristics and long-term results of GC treatment.

AIM

To establish the features of H. pylori infection in patients with GC and their correlations with clinical and morphological characteristics of diseases and long-term results of treatment.

METHODS

Of 109 patients with GC were included in a prospective cohort study. H. pylori in the GM and tumor was determined by rapid urease test and by immunohistochemically using the antibody to H. pylori. The results obtained were compared with the clinical and morphological characteristics and prognosis of GC. Statistical analysis was performed using the Statistica 10.0 software.

RESULTS

H. pylori was detected in the adjacent to the tumor GM in 84.5% of cases, of which a high degree of contamination was noted in 50.4% of the samples. Coccoid forms of H. pylori were detected in 93.4% of infected patients, and only coccoid-in 68.9%. It was found that a high degree of GM contamination by the coccoid forms of H. pylori was observed significantly more often in diffuse type of GC (P = 0.024), in poorly differentiated GC (P = 0.011), in stage T3-4 (P = 0.04) and in N1 (P = 0.011). In cases of moderate and marked concentrations of H. pylori in GM, a decrease in 10-year relapse free and overall survival from 55.6% to 26.3% was observed (P = 0.02 and P = 0.07, respectively). The relationship between the severity of the GM contamination by the spiral-shaped forms of H. pylori and the clinical and morphological characteristics and prognosis of GC was not revealed.

CONCLUSION

The data obtained indicates that H. pylori may be associated not only with induction but also with the progression of GC.

Bispecific antibody targeting TROP2xCD3 suppresses tumor growth of triple negative breast cancer

BACKGROUND

Triple negative breast cancer (TNBC) is a subtype of breast cancers with poor prognosis and targeted drug therapies are limited. To develop novel and efficacious therapies for TNBC, we developed a bispecific antibody F7AK3 that recognizes both trophoblast cell surface antigen 2 (TROP2) and CD3 and evaluated its antitumor activities both in vitro and in vivo.

METHODS

The binding affinities of F7AK3 to the two targets, TROP2 and CD3, were evaluated by surface plasmon resonance. Binding of F7AK3 to TNBC cells and T cells were evaluated by flow cytometry. Immunofluorescent staining was performed to demonstrate the interactions between T cells with TNBC cells. The cytotoxicity of T cells against TNBC cell lines and primary tumor cells mediated by F7AK3 were determined in vitro. In vivo antitumor activity of F7AK3 was investigated in a xenograft TNBC tumor model, using immunodeficient mice that were reconstituted with human peripheral blood mononuclear cells.

RESULTS

We demonstrated that F7AK3 binds specifically to human TROP2 and CD3 antigens, as well as TNBC cell lines and primary tumor cells. Human T cells can only be activated by F7AK3 in the presence of target tumor cells. F7AK3 recruits T cells to TROP2⁺ tumor cells in vitro and into tumor tissues in vivo. Antitumor growth activity of F7AK3 is observed in a xenograft TNBC tumor model.

CONCLUSION

This study showed the antitumor potential of an anti-TROP2xCD3 bispecific antibody F7AK3 to TNBC tumor cells both in vitro and in vivo. These data demonstrate that F7AK3 has the potential to treat TNBC patients, which warrants further preclinical and clinical evaluation of the F7AK3 in advanced or metastatic TNBC patients.

Novel Immune Infiltrating Cell Signature Based on Cell Pair Algorithm Is a Prognostic Marker in Cancer

Tumor-infiltrating immune cells (TIICs) have become an important source of markers for predicting the clinical outcomes of cancer patients. However, measurements of cellular heterogeneity vary due to the frequently updated reference genomes and gene annotations. In this study, we systematically collected and evaluated the infiltration pattern of 65 immune cells. We constructed the Immune Cell Pair (ICP) score based on the cell pair algorithm in 3,715 samples and across 12 independent cancer types, among which, the ICP score from six cancer types was further validated in 2,228 GEO samples. An extensive tumorigenic and immunogenomic analysis was subsequently conducted. As a result, the ICP score showed a robust reliability and efficacy in predicting the survival of patients with gliomas, in pan-cancer samples, and six independent cancer types. Notably, the ICP score was correlated with the genomic alteration features in gliomas. Moreover, the ICP score exhibited a remarkable association with multiple immunomodulators that could potentially mediate immune escape. Finally, the ICP score predicted immunotherapeutic responses with a high sensitivity, allowing a useful tool for predicting the overall survival and guiding immunotherapy for cancer patients.

Neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios as predictors of outcomes in inflammatory breast cancer

Background: Inflammatory breast cancer (IBC) is uncommon, aggressive and associated with poor survival outcomes. The lack of prognostic biomarkers and therapeutic targets specific to IBC is an added challenge for clinical practice and research. Inflammatory biomarkers such as neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios (NLR and PLR) demonstrated independent prognostic impact for survival in breast cancer. In our study, these biomarkers were investigated in a cohort of patients with nonmetastatic IBC. Methods: A retrospective cohort of 102 IBC patients with nonmetastatic disease was conducted at the Mohammed VI University Hospital (Oujda, Morocco) between January 2010 and December 2014. NLR and PLR were obtained from blood cell count at baseline before neoadjuvant chemotherapy (NACT) from patients' medical records. The receiver operating characteristic was used to find the optimal cut-off. Correlation between these blood-based biomarkers and response to NACT was analyzed by Chi-squared and Fisher's exact test. Their prognostic value for predicting disease-free survival (DFS) and overall survival (OS) was performed based on Cox regression models. Results: Totally, 102 patients with IBC were included in the analysis. Pathologic complete response (pCR) after NACT, defined by the absence of an invasive tumor in the breast tissues and nodes after surgery (ypT0 ypN0), was observed in eight patients (7.8%). NACT response was found to be associated with menopausal status (p = 0.039) and nodal status (p < 0.001). Patients with a low NLR had a higher pCR rate as compared with the high-NLR group (p = 0.043). However, the pCR rate was not significantly associated with age (p = 0.122), tumor side (p = 0.403), BMI (p = 0.615), histological grade (p = 0.059), hormone receptors status (p = 0.206), HER2 (p = 0.491) and PLR (p = 0.096). Pre-treatment blood-based NLR of 2.28 was used as the cut-off value to discriminate between high and low NLR according to the receiver operating characteristic curves. Similarly, a value of 178 was used as the cut off for PLR. Patients with low-NLR had a significantly better 5-year DFS (p < 0.001) and OS (p < 0.001) than the high-NLR group. Moreover, low-PLR was significantly associated with higher DFS (p = 0.001) and OS (p = 0.003). The NLR showed a significant prognostic impact for DFS (HR: 2.57; 95% CI: 1.43-4.61; p = 0.01) and for OS (HR: 2.92; 95% CI: 1.70-5.02; p < 0.001). Similarly, a meaningful association between PLR and 5-year DFS (HR: 1.95; 95% CI: 1.10-3.46; p = 0.021) and OS (HR: 1.82; 95% CI: 1.06-3.14; p = 0.03) was noticed. Conclusions: High NLR and PLR were found associated with reduced DFS and OS in nonmetastatic IBC. Further studies are awaited to confirm these findings.

Multi-Class Cell Detection Using Spatial Context Representation

In digital pathology, both detection and classification of cells are important for automatic diagnostic and prognostic tasks. Classifying cells into subtypes, such as tumor cells, lymphocytes or stromal cells is particularly challenging. Existing methods focus on morphological appearance of individual cells, whereas in practice pathologists often infer cell classes through their spatial context. In this paper, we propose a novel method for both detection and classification that explicitly incorporates spatial contextual information. We use the spatial statistical function to describe local density in both a multi-class and a multi-scale manner. Through representation learning and deep clustering techniques, we learn advanced cell representation with both appearance and spatial context. On various benchmarks, our method achieves better performance than state-of-the-arts, especially on the classification task. We also create a new dataset for multi-class cell detection and classification in breast cancer and we make both our code and data publicly available.

Prognostic role of lymphocyte to monocyte ratio in feline high-grade lymphomas

The lymphocyte to monocyte ratio (LMR) is a useful prognostic marker of various cancers in human and canine patients. This study aimed to determine whether this ratio could predict disease outcomes in cats with high-grade lymphoma. Medical records of 33 cats diagnosed with high-grade lymphoma were retrospectively analyzed. The prognostic influence of LMR and other clinicopathological data on the time to progression (TTP) and overall survival (OS) was studied using the Kaplan-Meier curves. The optimal cutoff value of this ratio was 3.4, which corresponded to the maximum sensitivity (1.000) and specificity (0.611) of the LMR for predicting median OS days, using receiver operating characteristic analysis. A univariate analysis demonstrated that cats with a low LMR had significant reductions in both TTP [hazard ration (HR) = 3.403, 95% confidence interval (CI): 1.502 to 8.720; P = 0.003] and OS (HR = 3.418, 95% CI: 1.433 to 9.449, P = 0.005). In multivariate analysis, independent predictors of OS included LMR (HR = 2.889, 95% CI: 1.048 to 8.843, P = 0.040), clinical stage (HR = 0.330, 95% CI: 0.118 to 0.960, P = 0.042), and age (HR = 4.151, 95% CI: 1.574 to 11.888, P = 0.004).

Correlation analysis of RDM1 gene with immune infiltration and clinical prognosis of hepatocellular carcinoma

Purpose: Liver hepatocellular carcinoma (LIHC) is one of the most common primary malignant liver tumors worldwide. The RAD52 motif-containing protein 1 (RDM1) has been shown to play a role in mediating DNA damage repair and homologous recombination. The present study was designed to determine the expression of RDM1 and its prognostic value as well as its relationship with immune infiltration in LIHC patients.

Methods: Oncomine and Tumor Immunoassay Resource were used to assess the expression of RDM1. PrognoScan and Kaplan–Meier bioinformatics database were used to analyze the impact of clinical influencing factors on prognosis. Finally, the Tumor Immune Assessment Resource (TIMER) and Gene Expression Analysis Interactive Analysis (GEPIA) databases were used to detect the correlation between the expression of RDM1 and expression of marker genes related to immune infiltration. Immunohistochemistry (IHC) method was used to detect the expression level of RDM1 in 90 cases of hepatocellular carcinoma and adjacent normal liver tissues.

Results: RDM1 expression was up-regulated in most cancers. The expression of RDM1 was remarkably higher than that of the corresponding normal control genes in LIHC tissues. The increase in RDM1 messenger RNA (mRNA) expression was closely related to the decreases in overall survival (OS) and progression-free survival (PFS). Additionally, the increase in RDM1 mRNA expression was closely related to the infiltration levels of macrophages, CD8⁺ T cells and B cells and was positively correlated with a variety of immune markers in LIHC.

Conclusion: The findings of the present study demonstrate that RDM1 is a potentially valuable prognostic biomarker that can help determine the progression of cancer and is associated with immune cell infiltration in LIHC.

Role of neutrophil-to-lymphocyte ratio as a prognostic biomarker in patients with breast cancer receiving neoadjuvant chemotherapy: a meta-analysis

OBJECTIVE

The neutrophil-to-lymphocyte ratio (NLR) is recognised as a suitable prognostic biomarker in patients with breast cancer. Nevertheless, the efficacy of this biomarker in predicting the pathological complete response (pCR) and survival in patients with breast cancer receiving neoadjuvant chemotherapy (NACT) is still controversial. This meta-analysis aimed to identify the association between baseline NLR and the prognosis of patients with breast cancer treated with NACT.

DESIGN

Meta-analysis.

DATA SOURCES

Relevant literature published before 1 May 2021 was searched using the Cochrane Library, Embase, PubMed and the Web of Science databases.

ELIGIBILITY CRITERIA

All studies involving patients with breast cancer treated with NACT and peripheral blood pretreatment NLR recorded as a dichotomous variable were included.

DATA EXTRACTION AND SYNTHESIS

Two researchers independently extracted and evaluated OR/HR and its 95% CIs of survival outcomes and clinicopathological parameters.

RESULTS

A total of 19 studies were identified. From each study, the impact of NLR on the pCR, OR and HR, with their 95% CIs were extracted and combined using either a random or fixed-effects model. The results indicate that a higher pCR in patients with a low NLR (OR 1.620, 95% CI 1.209 to 2.169, p＜0.001). In addition, an elevated NLR predicted lower disease-free survival (HR 2.269, 95% CI 1.557 to 3.307, p<0.001) and overall survival (HR 1.691, 95% CI 1.365 to 2.096, p<0.001) in patients with breast cancer treated with NACT.

CONCLUSIONS

NLR is a suitable biomarker for predicting pCR and survival in patients with breast cancer receiving NACT.

Molecular correlates of response to eribulin and pembrolizumab in hormone receptor-positive metastatic breast cancer

Immune checkpoint inhibitors (ICIs) have minimal therapeutic effect in hormone receptor-positive (HR+ ) breast cancer. We present final overall survival (OS) results (n = 88) from a randomized phase 2 trial of eribulin ± pembrolizumab for patients with metastatic HR+ breast cancer, computationally dissect genomic and/or transcriptomic data from pre-treatment tumors (n = 52) for molecular associations with efficacy, and identify cytokine changes differentiating response and ICI-related toxicity (n = 58). Despite no improvement in OS with combination therapy (hazard ratio 0.95, 95% CI 0.59-1.55, p = 0.84), immune infiltration and antigen presentation distinguished responding tumors, while tumor heterogeneity and estrogen signaling independently associated with resistance. Moreover, patients with ICI-related toxicity had lower levels of immunoregulatory cytokines. Broadly, we establish a framework for ICI response in HR+ breast cancer that warrants diagnostic and therapeutic validation. ClinicalTrials.gov Registration: NCT03051659.

Prognostic Value of Inflammatory Biomarkers in Patients With Stage I Lung Adenocarcinoma Treated With Surgical Dissection

Objective

Inflammation plays a crucial role in tumorigenesis and progression. Our purpose was to investigate the prognostic value of neutrophil-to-lymphocyte ratio (NLR), systemic inflammation response index (SIRI) and systemic immune-inflammation index (SII), and develop a nomogram to predict the cancer-specific survival (CSS) and disease-free survival (DFS) of stage I lung adenocarcinoma patients.

Methods

1431 patients undergoing surgical resection with pathologically confirmed stage I lung adenocarcinoma were reviewed. The optimal cut-off values for NLR, SII, and SIRI were defined by the receiver operating characteristic (ROC) curve. Cox proportional hazards regression analyses were performed to recognize factors significantly correlated with CSS and DFS to construct the nomogram. The value of adjuvant chemotherapy on model-defined high-risk and low-risk patients was further explored.

Results

The cohort had a median follow-up time of 63 months. Multivariate analysis revealed that higher NLR (≥2.606), higher SIRI (≥0.705), higher SII (≥580.671), later T stage, histological pattern with solid or micropapillary components and radiologic features with solid nodules were significantly associated with worse CSS and DFS. The concordance index (C-index) of the nomogram established by all these factors was higher than that of the TNM staging system both in CSS (validation set 0.778 vs 0.652) and DFS (validation set 0.758 vs 0.695). Furthermore, the value of the established nomogram on risk stratification in stage I lung adenocarcinoma patients was validated.

Conclusions

Higher NLR, SII and SIRI pretreatment were associated with worse survival outcomes. A practical nomogram based on these three inflammatory biomarkers may help clinicians to precisely stratify stage I lung adenocarcinoma patients into high- and low-risk and implement individualized treatment.

Landscape of Immune Microenvironment Under Immune Cell Infiltration Pattern in Breast Cancer

Background

Increasing evdence supports the suggestion that the immune cell infiltration (ICI) patterns play a pivotal role in tumor progression in breast cancer (BRCA). Nonetheless, there has been no comprehensive analysis of the ICI patterns effects on the clinical outcomes and immunotherapy.

Methods

Multiomic data for BRCA samples were downloaded from TCGA. ESTIMATE algorithm, ssGSEA method, and CIBERSORT analysis were used to uncover the landscape of the tumor immune microenvironment (TIME). BRCA subtypes based on the ICI pattern were identified by consensus clustering and principal-component analysis was performed to obtain the ICI scores to quantify the ICI patterns in individual tumors. Their prognostic value was validated by the Kaplan-Meier survival curves. Gene set enrichment analysis (GSEA) was applied for functional annotation. Immunophenoscore (IPS) was employed to explore the immunotherapeutic role of the ICI scores. Finally, the mutation data was analyzed by using the “maftools” R package.

Results

Three different immune infiltration patterns with a distinct prognosis and biological signature were recognized among 1,198 BRCA samples. The characteristics of TIME under these three patterns were highly consistent with three known immune profiles: immune- excluded, immune-desert, and immune-inflamed phenotypes, respectively. The identification of the ICI patterns within individual tumors based on the ICI score, developed under the ICI-related signature genes, contributed into dissecting biological processes, clinical outcome, immune cells infiltration, immunotherapeutic effect, and genetic variation. High ICI score subtype, characterized with a suppression of immunity, suggested an immune-exhausted phenotype. Abundant effective immune cells were discovered in the low ICI score patients, which corresponded to an immune-activated phenotype and might present an immunotherapeutic advantage. Immunophenoscore was implemented as a surrogate of immunotherapeutic outcome, low-ICI scores samples obtained a significantly higher immunophenoscore. Enrichment of the JAK/STAT and VEGF signal pathways were activated in the ICI low-score subgroup. Finally, the synergistic effect between the ICI score and the tumor mutation burden (TMB) was confirmed.

Conclusion

This work comprehensively elucidated that the ICI patterns served as an indispensable player in complexity and diversity of TIME. Quantitative identification of the ICI patterns in individual tumor will contribute into mapping the landscape of TIME further optimizing precision immunotherapy.

Single-Cell RNA Sequencing Reveals the Migration of Osteoclasts in Giant Cell Tumor of Bone

Giant cell tumor of bone (GCTB) is benign tumor that can cause significant osteolysis and bone destruction at the epiphysis of long bones. Osteoclasts are thought to be highly associated with osteolysis in GCTB. However, the migration of osteoclasts in GCTB remains unclear. A deeper understanding of the complex tumor microenvironment is required in order to delineate the migration of osteoclasts in GCTB. In this study, samples were isolated from one patient diagnosed with GCTB. Single-cell RNA sequencing (scRNA-seq) was used to detect the heterogeneity of GCTB. Multiplex immunofluorescence staining was used to evaluate the cell subtypes identified by scRNA-seq. A total of 8,033 cells were obtained from one patient diagnosed with GCTB, which were divided into eight major cell types as depicted by a single-cell transcriptional map. The osteoclasts were divided into three subsets, and their differentiation trajectory and migration status were further analyzed. Osteoclast migration may be regulated via a series of genes associated with cell migration. Furthermore, four signaling pathways (RANKL, PARs, CD137 and SMEA3 signaling pathway) were found to be highly associated with osteoclast migration. This comprehensive single-cell transcriptome analysis of GCTB identified a series of genes associated with cell migration as well as four major signaling pathways that were highly related to the migration of osteoclasts in GCTB. Our findings broaden the understanding of GCTB bionetworks and provides a theoretical basis for anti-osteolysis therapy against GCTB in the future.