Development of a multiparametric model for predicting the response to neoadjuvant chemotherapy in breast cancer.

Background: Choosing the appropriate treatment early and predicting the efficacy of neoadjuvant chemotherapy (NAC) for locally advanced breast cancer patients are of particular importance for clinicians. Developing and validating a multiparametric model for predicting NAC would be very meaningful for clinical practice. Methods: This study included 91 patients with locally advanced breast cancer treated from 2016 to 2020. The correlation between multiparametric characteristics and the efficacy of NAC was examined. The data were randomly divided into training and validation sets. A least absolute shrinkage and selection operator (LASSO) regression analysis was used for the variable screening. A multivariable logistic regression analysis was used to construct the model. Calibration and decision curves were used to assess the performance of the established model. Results: Lymph node metastasis, the first standard apparent diffusion coefficient (ADC) at the baseline, the change in the standard ADC at the first follow-up, the change in tumor volume at the first follow-up, and the clinical stage of the tumor at the baseline were selected for inclusion in the model. In the receiver operating characteristic (ROC) analysis, the areas under the curve (AUCs) were 0.984 [95% confidence interval (CI): 0.958-1] and 0.815 (95% CI: 0.509-1) for the primary and validation cohorts, respectively. The utility of the established model was confirmed by calibration and decision curves, and a nomogram was obtained. Conclusions: A multiparametric model based on clinical-pathological-magnetic resonance imaging (MRI) features was established to predict the effect of NAC in patients with locally advanced breast cancer.

Analyses of hypoxia-related risk factors and clinical relevance in breast cancer.

Introduction: Hypoxia plays an important role in the heterogeneity, relapse, metastasis, and drug resistance of breast cancer. In this study, we explored the hypoxia-related biological signatures in different subtypes of breast cancer and identified the key prognostic factors by bioinformatics methods. Methods: Based on The Cancer Genome Atlas (TCGA) Breast Cancer datasets, we divided the samples into immune-activated/suppressed populations by single-sample gene set enrichment analysis (ssGSEA) and then used hierarchical clustering to further identify hypoxic/non-hypoxic populations from the immune-suppressed samples. A hypoxia related risk model of breast cancer was constructed. Results: Nuclear factor interleukin-3 regulated (NFIL3), serpin family E member 1 (SERPINE1), FOS, biglycan (BGN), epidermal growth factor receptor (EGFR), and sushi-repeat-containing protein, X-linked (SRPX) were identified as key hypoxia-related genes. Margin status, American Joint Committee on Cancer (AJCC) stage, hypoxia status, estrogen receptor/progesterone receptor (ER/PR) status, NFIL3, SERPINE1, EGFR, and risk score were identified as independent prognostic indicators for breast cancer patients. The 3- and 5-year survival curves of the model and immunohistochemical staining on the breast cancer microarray verified the statistical significance and feasibility of our model. Among the different molecular types of breast cancer, ER/PR+ and HER2+ patients might have higher hypoxia-related risk scores. ER/PR-negative samples demonstrated more activated immune-related pathways and better response to most anticancer agents. Discussion: Our study revealed a novel risk model and potential feasible prognostic factors for breast cancer and might provide new perspectives for individual breast cancer treatment.

Breast Cancer Stem Cells Secrete MIF to Mediate Tumor Metabolic Reprogramming That Drives Immune Evasion.

Reprogramming of energy metabolism exerts pivotal functions in cancer progression and immune surveillance. Identification of the mechanisms mediating metabolic changes in cancer may lead to improved strategies to suppress tumor growth and stimulate antitumor immunity. Here, it was observed that the secretomes of hypoxic breast cancer cells and breast cancer stem cells (BCSC) induced reprogramming of metabolic pathways, particularly glycolysis, in normoxic breast cancer cells. Screening of the BCSC secretome identified MIF as a pivotal factor potentiating glycolysis. Mechanistically, MIF increased c-MYC-mediated transcriptional upregulation of the glycolytic enzyme aldolase C by activating WNT/ß-catenin signaling. Targeting MIF attenuated glycolysis and impaired xenograft growth and metastasis. MIF depletion in breast cancer cells also augmented intratumoral cytolytic CD8+ T cells and proinflammatory macrophages while decreasing regulatory T cells and tumor-associated neutrophils in the tumor microenvironment. Consequently, targeting MIF improved the therapeutic efficacy of immune checkpoint blockade in triple-negative breast cancer. Collectively, this study proposes MIF as an attractive therapeutic target to circumvent metabolic reprogramming and immunosuppression in breast cancer. SIGNIFICANCE: MIF secreted by breast cancer stem cells induces metabolic reprogramming in bulk tumor cells and engenders an immunosuppressive microenvironment, identifying MIF targeting as a strategy to improve immunotherapy efficacy in breast cancer.

LINC00460-FUS-MYC feedback loop drives breast cancer metastasis and doxorubicin resistance.

Therapeutic resistance and metastasis largely contribute to mortality from breast cancer and therefore understanding the underlying mechanisms of such remains an urgent challenge. By cross-analysis of TCGA and GEO databases, LINC00460 was identified as an oncogenic long non-coding RNA, highly expressed in Doxorubicin resistant breast cancer. LINC00460 was further demonstrated to promote stem cell-like and epithelial-mesenchymal transition (EMT) characteristics in breast cancer cells. LINC00460 interacts with FUS protein with consequent enhanced stabilization, which further promotes MYC mRNA maturation. LINC00460 expression was transcriptionally enhanced by c-MYC protein, forming a positive feedback loop to promote metastasis and Doxorubicin resistance. LINC00460 depletion in Doxorubicin-resistant breast cancer cells restored sensitivity to Doxorubicin and increased the efficacy of c-MYC inhibitor therapy. Collectively, these findings implicate LINC00460 as a promising prognostic biomarker and potential therapeutic target to overcome Doxorubicin resistance in breast cancer.

Association between platelet-to-lymphocyte ratio and outcomes in HER2-positive advanced breast cancer patients treated with pyrotinib: a retrospective study.

Background: Peripheral blood biomarkers have been reported to be associated with the prognosis of breast cancer (BC) patients, but a few findings remain controversial. This study aimed to explore the correlation between peripheral blood indicators and treatment outcomes in human epidermal growth factor receptor 2 (HER2)-positive advanced BC patients treated with pyrotinib. Methods: This was a retrospective cohort study including 156 HER2-positive advanced BC patients who treated with pyrotinib between March 2019 and May 2021. The baseline clinical characteristics including age, hormone receptor (HR) status, Ki-67, sites of metastasis, antitumor therapies and peripheral blood parameters including neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), monocyte to lymphocyte ratio (MLR), the product of neutrophil, platelet, and monocyte counts divided by lymphocyte count [pan-immune-inflammation value (PIV)] were collected. Tumor response was assessed every two cycles during treatment period. Follow-up was performed every 2 months to record survival status. All patients were followed up until death or time of data lock. Results: Low PLR was associated with better disease control rate (P=0.005). Univariate analysis showed that high MLR (P=0.004), PLR (P=0.003), or PIV (P=0.02), low lymphocyte count (P=0.025), more than two metastatic sites (P<0.001), and presence of liver metastasis (P<0.001) or brain metastasis (P<0.001) were associated with poor progression-free survival (PFS). Multivariate analysis showed that only high PLR was an independent factor for poor PFS [hazard ratio =0.63; 95% confidence interval (CI): 0.41-0.97; P=0.038]. For overall survival (OS), univariate analysis showed that high NLR (P=0.001), MLR (P=0.005), PLR (P<0.001), or PIV (P=0.018), more than two metastatic sites (P=0.001), presence of liver metastasis (P=0.004) or brain metastasis (P=0.007), and pyrotinib monotherapy (P=0.036) were associated with worse OS. Multivariate analysis showed that PLR (hazard ratio =0.37; 95% CI: 0.14-0.94; P=0.037), number of metastatic sites (hazard ratio =2.84; 95% CI: 1.02-7.94; P=0.046) and treatment regimens (hazard ratio =0.15; 95% CI: 0.03-0.73; P=0.019) were independent factors. Conclusions: High PLR is associated with poor treatment response and is an independent unfavorable prognostic factor in HER2-positive advanced BC patients treated with pyrotinib. The findings herein indicate that patients with higher PLR are less likely to benefit from pyrotinib-based therapy and may be helpful in identifying the effective population in clinical practice.

Pharmacokinetics, pharmacodynamics and efficacy of pemigatinib (a selective inhibitor of fibroblast growth factor receptor 1-3) monotherapy in Chinese patients with advanced solid tumors: a phase i clinical trial.

Pemigatinib is a selective fibroblast growth factor receptor (FGFR)1-3 inhibitor and has demonstrated acceptable tolerability and clinical activity in advanced solid tumors in Western population. This phase I trial evaluated pharmacokinetics/pharmacodynamics (PK/PD) characteristics, preliminary safety and efficacy of pemigatinib in Chinese patients with advanced, solid tumors. Patients with unresectable advanced or metastatic solid tumors bearing FGF/FGFR1-3 alterations received oral pemigatinib at 13.5 mg once daily (QD) on a 2-weeks-on/1-week-off schedule. The primary endpoint was PK/PD characteristics; secondary endpoints were safety and efficacy. Twelve patients were enrolled (median age: 61 years, 58.3% males). PK data demonstrated pemigatinib (13.5 mg QD) was rapidly absorbed with a geometric mean elimination half-life of 11.3 h. The geometric mean values of maximum serum concentration and area under the plasma concentration-time curve from 0 to 24 h at steady state were 215.1 nmol/L and 2636.9 h·nmol/L, respectively. The mean clearance adjusted by bioavailability at steady state was low (11.8 L/h), and the apparent oral volume of distribution was moderate (170.5 L). The PD marker, serum phosphate level, increased on days 8 and 15 of cycle 1 (mean: 2.25 mg/dL, CV% [percent coefficient of variation]: 31.3%) and decreased to baseline post 1 week off. Three (25.0%) patients experienced grade ≥ 3 treatment-emergent adverse events. Partial response was confirmed in one patient with FGFR1-mutant esophageal carcinoma and one with FGFR2-mutant cholagiocarcinoma. Pemigatinib had similar PK/PD characteristics to Western population and demonstrated an acceptable safety profile and potential anti-cancer benefit in Chinese patients with FGF/FGFR1-3 altered, advanced, solid tumor. (ClinicalTrials.gov: NCT04258527 [prospectively registered February 6, 2020]).

LncRNA H19 Regulates Breast Cancer DNA Damage Response and Sensitivity to PARP Inhibitors via Binding to ILF2.

Although DNA damage repair plays a critical role in cancer chemotherapy, the function of lncRNAs in this process remains largely unclear. In this study, in silico screening identified H19 as an lncRNA that potentially plays a role in DNA damage response and sensitivity to PARP inhibitors. Increased expression of H19 is correlated with disease progression and with a poor prognosis in breast cancer. In breast cancer cells, forced expression of H19 promotes DNA damage repair and resistance to PARP inhibition, whereas H19 depletion diminishes DNA damage repair and increases sensitivity to PARP inhibitors. H19 exerted its functional roles via direct interaction with ILF2 in the cell nucleus. H19 and ILF2 increased BRCA1 stability via the ubiquitin-proteasome proteolytic pathway via the H19- and ILF2-regulated BRCA1 ubiquitin ligases HUWE1 and UBE2T. In summary, this study has identified a novel mechanism to promote BRCA1-deficiency in breast cancer cells. Therefore, targeting the H19/ILF2/BRCA1 axis might modulate therapeutic approaches in breast cancer.

Immune microenvironment and clinical feature analyses based on a prognostic model in lymph node-positive breast cancer.

Background: If lymph node metastasis occurs in breast cancer patients, the disease can progress rapidly. Based on the infiltrative immune cells of breast cancer patients with lymph node positivity, we constructed the LNPRS for selecting prognostic predictors. Methods: The LNPRS was established and the predictive value of the LNPRS was verified by independent testing cohorts. A nomogram was also established to confirm the therapeutic guidance significance of the LNPRS. The correlation of the LNPRS with tumor mutation burden, immune microenvironment score, immune checkpoints, the proportion of tumor-infiltrating immune cells, and GSEA and GSVA enrichment pathways were also evaluated. Results: In the training cohort, the overall survival of breast cancer patients who had high LNPRS was shorter than that of patients who had low LNPRS (7.98 years versus 20.42 years, P-value< 8.16E-11). The AUC values for 5-, 10-, and 15-years were 0.787, 0.739, and 0.800, respectively. The ability to predict prognosis for the LNPRS was also tested in 3 independent testing cohorts. Furthermore, the predictive value of the LNPRS for chemotherapy and immunotherapy was also proven. The GSEA and GSVA showed that the LNPRS was closely related to the activation of T and B lymphocytes and IFN-γ secretion. Moreover, breast cancer patients with low LNPRS had higher TME scores than those with high LNPRS. Conclusion: We can conclude that the LNPRS is a robust prognostic biomarker in breast cancer patients with positive lymph nodes and may be helpful for patients to make a clinical decision.

Paracrine secretion of IL8 by breast cancer stem cells promotes therapeutic resistance and metastasis of the bulk tumor cells.

BACKGROUND: Breast tumors consist of heterogeneous cellular subpopulations that differ in molecular properties and functional attributes. Cancer stem cells (CSCs) play pivotal roles in cancer therapeutic failure and metastasis. However, it remains indeterminate how CSCs determine the progression of the bulk cancer cell population. METHODS: Co-culture systems in vitro and co-implantation systems in vivo were designed to characterize the interactions between breast cancer stem cells (BCSCs) and bulk cancer cells. RNA sequencing was performed to study the functional and mechanistic implications of the BCSC secretome on bulk cancer cells. A cytokine antibody array was employed to screen the differentially secreted cytokines in the BCSC secretome. Tail vein injection metastatic models and orthotopic xenograft models were applied to study the therapeutic potential of targeting IL8. RESULTS: We identified that the BCSC secretome potentiated estrogen receptor (ER) activity in the bulk cancer cell population. The BCSC secretome rendered the bulk cancer cell population resistant to anti-estrogen and CDK4/6 inhibitor therapy; as well as increased the metastatic burden attributable to bulk cancer cells. Screening of the BCSC secretome identified IL8 as a pivotal factor that potentiated ERα activity, endowed tamoxifen resistance and enhanced metastatic burden by regulation of bulk cancer cell behavior. Pharmacological inhibition of IL8 increased the efficacy of fulvestrant and/or palbociclib by reversing tamoxifen resistance and abrogated metastatic burden. CONCLUSION: Taken together, this study delineates the mechanism by which BCSCs determine the therapeutic response and metastasis of bulk cancer cells; and thereby suggests potential therapeutic strategies to ameliorate breast cancer outcomes. Video Abstract.

Immune checkpoints expression patterns in early-stage triple-negative breast cancer predict prognosis and remodel the tumor immune microenvironment.

Background: Currently, targeting immune checkpoint molecules holds great promise for triple-negative breast cancer (TNBC). However, the expression landscape of immune checkpoint genes (ICGs) in TNBC remains largely unknown. Method: Herein, we systematically investigated the ICGs expression patterns in 422 TNBC samples. We evaluated the ICGs molecular typing based on the ICGs expression profile and explored the associations between ICGs molecular subtypes and tumor immune characteristics, clinical significance, and response to immune checkpoint inhibitors (ICIs). Results: Two ICGs clusters and two ICGs-related gene clusters were determined, which were involved in different survival outcomes, biological roles and infiltration levels of immune cells. We established a quantification system ICGs riskscore (named IRS) to assess the ICGs expression patterns for individuals. TNBC patients with lower IRS were characterized by increased immune cell infiltration, favorable clinical outcomes and high sensitivity to ICIs therapy. We also developed a nomogram model combining clinicopathological variables to predict overall survival in TNBC. Genomic feature analysis revealed that high IRS group presented an increased tumor mutation burden compared with the low IRS group. Conclusion: Collectively, dissecting the ICGs expression patterns not only provides a new insight into TNBC subtypes but also deepens the understanding of ICGs in the tumor immune microenvironment.

Systematic Investigation of the Multifaceted Role of SOX11 in Cancer.

SRY-box transcription factor 11 (SOX11), as a member of the SOX family, is a transcription factor involved in the regulation of specific biological processes and has recently been found to be a prognostic marker for certain cancers. However, the roles of SOX11 in cancer remain controversial. Our study aimed to explore the various aspects of SOX11 in pan-cancer. The expression of SOX11 was investigated by the Genotype Tissue-Expression (GTEX) dataset and the Cancer Genome Atlas (TCGA) database. The protein level of SOX11 in tumor tissues and tumor-adjacent tissues was verified by human pan-cancer tissue microarray. Additionally, we used TCGA pan-cancer data to analyze the correlations among SOX11 expression and survival outcomes, clinical features, stemness, microsatellite instability (MSI), tumor mutation burden (TMB), mismatch repair (MMR) related genes and the tumor immune microenvironment. Furthermore, the cBioPortal database was applied to investigate the gene alterations of SOX11. The main biological processes of SOX11 in cancers were analyzed by Gene Set Enrichment Analysis (GSEA). As a result, aberrant expression of SOX11 has been implicated in 27 kinds of cancer types. Aberrant SOX11 expression was closely associated with survival outcomes, stage, tumor recurrence, MSI, TMB and MMR-related genes. In addition, the most frequent alteration of the SOX11 genome was mutation. Our study also showed the correlations of SOX11 with the level of immune infiltration in various cancers. In summary, our findings underline the multifaceted role and prognostic value of SOX11 in pan-cancer.

The single-atom iron nanozyme mimicking peroxidase remodels energy metabolism and tumor immune landscape for synergistic chemodynamic therapy and photothermal therapy of triple-negative breast cancer.

Chemotherapy, as one main strategy to relieve tumor progression, has a weak effect on triple-negative breast cancer (TNBC) chest wall metastasis. The development of near-infrared (NIR) light-responsive nanomaterials for chemodynamic therapy (CDT) and photothermal therapy (PTT) is a promising platform but still challenging in biomedicine. This study reports a peroxidase mimicking nanozyme (Fe-N-C SAzyme) against TNBC by CDT and PTT. Fe-N-C SAzyme generated reactive oxygen species (ROS) by decomposing H2O2 into hydroxyl radicals (•OH) and also induced light-to-heat conversion under the exposure of 808 nm laser irradiation. With these biological characteristics, the obtained Fe-N-C SAzymes displayed enhanced cell cytotoxicity and inhibition of cancer cell proliferation both in vitro and in vivo at a low dose of nanoagent and a moderate NIR laser power density. Besides, Fe-N-C nanoagent with its excellent ROS generation brought metabolic reprogramming of elevated glycolysis in tumor cells. In vivo experiments, when combined with PTT, the enhanced antitumor effect was found by the elimination of M-MDSC in tumor microenvironment. Fe-N-C SAzymes can serve as a new synergistic CDT and PTT nanoagent to simultaneously reprogram tumor metabolism and tumor microenvironment. It will provide prospects for chemodynamic/photothermal combined cancer therapy for TNBC chest wall metastasis based on the use of a single nanosystem.

Combination of Immune-Related Network and Molecular Typing Analysis Defines a Three-Gene Signature for Predicting Prognosis of Triple-Negative Breast Cancer.

Recent breakthroughs in immune checkpoint inhibitors (ICIs) have shown promise in triple-negative breast cancer (TNBC). Due to the intrinsic heterogeneity among TNBC, clinical response to ICIs varies greatly among individuals. Thus, discovering rational biomarkers to select susceptible patients for ICIs treatment is warranted. A total of 422 TNBC patients derived from The Cancer Genome Atlas (TCGA) database and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset were included in this study. High immunogenic gene modules were identified using weighted gene co-expression network analysis (WGCNA). Immune-related genes (IRGs) expression patterns were generated by consensus clustering. We developed a three-gene signature named immune-related gene panel (IRGP) by Cox regression method. Afterward, the associations of IRGP with survival outcomes, infiltration of immune cells, drug sensitivity, and the response to ICIs therapy were further explored. We found five high immunogenic gene modules. Two distinct IRGclusters and IRG-related genomic clusters were identified. The IRGP was constructed based on TAPBPL, FBP1, and GPRC5C genes. TNBC patients were then subdivided into high- and low-IRGriskscore subgroups. TNBC patients with low IRGriskscore had a better survival outcome, higher infiltration of immune cells, lower TP53 mutation rate, and more benefit from ICIs treatment than high IRGriskscore patients. These findings offer novel insights into molecular subtype of TNBC and provided potential indicators for guiding ICIs treatment.

Machine learning models based on immunological genes to predict the response to neoadjuvant therapy in breast cancer patients.

Breast cancer (BC) is the most common malignancy worldwide and neoadjuvant therapy (NAT) plays an important role in the treatment of patients with early BC. However, only a subset of BC patients can achieve pathological complete response (pCR) and benefit from NAT. It is therefore necessary to predict the responses to NAT. Although many models to predict the response to NAT based on gene expression determined by the microarray platform have been proposed, their applications in clinical practice are limited due to the data normalization methods during model building and the disadvantages of the microarray platform compared with the RNA-seq platform. In this study, we first reconfirmed the correlation between immune profiles and pCR in an RNA-seq dataset. Then, we employed multiple machine learning algorithms and a model stacking strategy to build an immunological gene based model (Ipredictor model) and an immunological gene and receptor status based model ICpredictor model) in the RNA-seq dataset. The areas under the receiver operator characteristic curves for the Ipredictor model and ICpredictor models were 0.745 and 0.769 in an independent external test set based on the RNA-seq platform, and were 0.716 and 0.752 in another independent external test set based on the microarray platform. Furthermore, we found that the predictive score of the Ipredictor model was correlated with immune microenvironment and genomic aberration markers. These results demonstrated that the models can accurately predict the response to NAT for BC patients and will contribute to individualized therapy.

Cancer stem cell regulated phenotypic plasticity protects metastasized cancer cells from ferroptosis.

Cancer cells display phenotypic equilibrium between the stem-like and differentiated states during neoplastic homeostasis. The functional and mechanistic implications of this subpopulation plasticity remain largely unknown. Herein, it is demonstrated that the breast cancer stem cell (BCSC) secretome autonomously compresses the stem cell population. Co-implantation with BCSCs decreases the tumor-initiating capacity yet increases metastasis of accompanying cancer cells, wherein DKK1 is identified as a pivotal factor secreted by BCSCs for such functions. DKK1-promotes differentiation is indispensable for disseminated tumor cell metastatic outgrowth. In contrast, DKK1 inhibitors substantially relieve the metastatic burden by restraining metastatic cells in the dormant state. DKK1 increases the expression of SLC7A11 to protect metastasizing cancer cells from lipid peroxidation and ferroptosis. Combined treatment with a ferroptosis inducer and a DKK1 inhibitor exhibits synergistic effects in diminishing metastasis. Hence, this study deciphers the contribution of CSC-regulated phenotypic plasticity in metastatic colonization and provides therapeutic approaches to limit metastatic outgrowth.

Expression Patterns of Ezrin and AJAP1 and Clinical Significance in Breast Cancer.

Ezrin and adherens junction-associated protein 1 (AJAP1) are structural proteins which are involved in numerous human malignancies. However, little is known about the relationship between them in breast cancer. This study was set out to investigate the relationship between them and to further explore the mechanism of AJAP1-mediating cytoskeleton in breast cancer progression. Ezrin and AJAP1 expressions were detected in 377 samples of breast cancer by immunohistochemistry, and different expression patterns between AJAP1 and Ezrin with clinicopathological parameters were analyzed. Besides, univariate and multivariate Cox models were used to evaluate their prognostic potential. Enzyme-linked immunosorbent assay, Western blot, qRT-PCR, and phalloidin staining of F-actin were used to explore the relationship and the mechanism between AJAP1 and Ezrin in cytoskeleton arrangement. 377 cases of breast cancer results showed that AJAP1 expression was negatively related with histological grade and lymph node involvement and could be an independent prognosis marker of breast cancer. AJAP1 expression tended to be higher in the Ezrin-negative expression case. Patients with AJAP1negative and Ezrinpositive expression had a worse prognosis (p < 0.0001) and shorter DFS (p = 0.015). More importantly, AJAP1 depletion increased the cell ability of F-actin formation through promoting Ezrin expression. AJAP1 depletion might mediate breast cancer malignancy potential through promoting Ezrin expression and cytoskeleton formation.

Unraveling the Expression Patterns of Immune Checkpoints Identifies New Subtypes and Emerging Therapeutic Indicators in Lung Adenocarcinoma.

Immune checkpoint genes (ICGs) play pivotal roles in tumor immune microenvironment (TIME), and thus, targeting them represents a promising strategy for cancer immunotherapy. However, the genetic landscape of ICGs in lung adenocarcinoma (LUAD) is still unknown. Herein, we comprehensively evaluated the ICG expression profiles of 1439 LUAD samples and linked ICG expression patterns with infiltration of immune cells, clinical features, and response to immune checkpoint blockade (ICB). The ICGscore was developed to quantify ICG expression patterns of individual patient by principal component analysis algorithms. Three distinct ICG expression patterns and three ICG-related genomic clusters were determined, which were implicated in different clinical outcomes, level of immune infiltrates, and biological process. LUAD patients were subdivided into high- and low-ICGscore subgroups. Patients with higher ICGscore were characterized by favorable survival outcomes, increased immune cell infiltration, and enhanced expression of ICGs. Further analysis revealed that lower ICGscore was associated with greater tumor mutation loads and higher mutation rates of TTN, KEAP1, and ZFHX4. High ICGscore has the potential to be a robust indicator in clinical benefit of immunotherapy. Taken together, unraveling the ICG expression patterns will advance our understanding of heterogeneity of TIME and guides more effective immunotherapeutic strategies in LUAD.

Clinical Significance and Prognostic Value of Human Soluble Resistance-Related Calcium-Binding Protein: A Pan-Cancer Analysis.

The soluble resistance-related calcium-binding protein (sorcin, SRI) serves as the calcium-binding protein for the regulation of calcium homeostasis and multidrug resistance. Although the mounting evidence suggests a crucial role of SRI in the chemotherapeutic resistance of certain types of tumors, insights into pan-cancer analysis of SRI are unavailable. Therefore, this study aimed to probe the multifaceted properties of SRI across the 33 cancer types. The SRI expression was analyzed via The Cancer Genome Atlas (TCGA) and Genotype Tissue-Expression (GTEX) database. The SRI genomic alterations and drug sensitivity analysis were performed based on the cBioPortal and the CellMiner database. Furthermore, the correlations among the SRI expression and survival outcomes, clinical features, stemness, tumor mutation burden (TMB), microsatellite instability (MSI), and immune cells infiltration were analyzed using TCGA data. The differential analysis showed that SRI was upregulated in 25 tumor types compared with the normal tissues. Aberrant expression of SRI was able to predict survival in different cancers. Further, the most frequent alteration of SRI genomic was amplification. Moreover, the aberrant SRI expression was related to stemness score, epithelial-mesenchymal-transition (EMT)-related genes, MSI, TMB, and tumor immune microenvironment in various types of cancer. TIMER database mining further found that the SRI expression was significantly correlated with the infiltration levels of various immune cells in certain types of cancer. Intriguingly, the SRI expression was negatively correlated with drug sensitivity of fluorouracil, paclitaxel, docetaxel, and isotretinoin. Our findings highlight the predictive value of SRI in cancer and provide insights for illustrating the role of SRI in tumorigenesis and drug resistance.

Corrigendum: Dissecting the Role of N6-Methylandenosine-Related Long Non-Coding RNAs Signature in Prognosis and Immune Microenvironment of Breast Cancer.

[This corrects the article DOI: 10.3389/fcell.2021.711859.].