Single-Cell RNA-Sequencing: Opening New Horizons for Breast Cancer Research.

Breast cancer is the most prevalent malignant tumor among women with high heterogeneity. Traditional techniques frequently struggle to comprehensively capture the intricacy and variety of cellular states and interactions within breast cancer. As global precision medicine rapidly advances, single-cell RNA sequencing (scRNA-seq) has become a highly effective technique, revolutionizing breast cancer research by offering unprecedented insights into the cellular heterogeneity and complexity of breast cancer. This cutting-edge technology facilitates the analysis of gene expression profiles at the single-cell level, uncovering diverse cell types and states within the tumor microenvironment. By dissecting the cellular composition and transcriptional signatures of breast cancer cells, scRNA-seq provides new perspectives for understanding the mechanisms behind tumor therapy, drug resistance and metastasis in breast cancer. In this review, we summarized the working principle and workflow of scRNA-seq and emphasized the major applications and discoveries of scRNA-seq in breast cancer research, highlighting its impact on our comprehension of breast cancer biology and its potential for guiding personalized treatment strategies.

Predicting tumor mutation burden and VHL mutation from renal cancer pathology slides with self-supervised deep learning.

BACKGROUND: Tumor mutation burden (TMB) and VHL mutation play a crucial role in the management of patients with clear cell renal cell carcinoma (ccRCC), such as guiding adjuvant chemotherapy and improving clinical outcomes. However, the time-consuming and expensive high-throughput sequencing methods severely limit their clinical applicability. Predicting intratumoral heterogeneity poses significant challenges in biology and clinical settings. Our aimed to develop a self-supervised attention-based multiple instance learning (SSL-ABMIL) model to predict TMB and VHL mutation status from hematoxylin and eosin-stained histopathological images. METHODS: We obtained whole slide images (WSIs) and somatic mutation data of 350 ccRCC patients from The Cancer Genome Atlas for developing SSL-ABMIL model. In parallel, 163 ccRCC patients from Clinical Proteomic Tumor Analysis Consortium cohort was used as independent external validation set. We systematically compared three different models (Wang-ABMIL, Ciga-ABMIL, and ImageNet-MIL) for their ability to predict TMB and VHL alterations. RESULTS: We first identified two groups of populations with high- and low-TMB (cut-off point = 0.9). In two independent cohorts, the Wang-ABMIL model achieved the highest performance with decent generalization performance (AUROC = 0.83 ± 0.02 and 0.8 ± 0.04 in predicting TMB and VHL, respectively). Attention heatmaps revealed that the Wang-ABMIL model paid the highest attention to tumor regions in high-TMB patients, while in VHL mutation prediction, non-tumor regions were also assigned high attention, particularly the stromal regions infiltrated by lymphocytes. CONCLUSIONS: Our results indicated that SSL-ABMIL can effectively extract histological features for predicting TMB and VHL mutation, demonstrating promising results in linking tumor morphology and molecular biology.

Artificial intelligence: illuminating the depths of the tumor microenvironment.

Artificial intelligence (AI) can acquire characteristics that are not yet known to humans through extensive learning, enabling to handle large amounts of pathology image data. Divided into machine learning and deep learning, AI has the advantage of handling large amounts of data and processing image analysis, consequently it also has a great potential in accurately assessing tumour microenvironment (TME) models. With the complex composition of the TME, in-depth study of TME contributes to new ideas for treatment, assessment of patient response to postoperative therapy and prognostic prediction. This leads to a review of the development of AI's application in TME assessment in this study, provides an overview of AI techniques applied to medicine, delves into the application of AI in analysing the quantitative and spatial location characteristics of various cells (tumour cells, immune and non-immune cells) in the TME, reveals the predictive prognostic value of TME and provides new ideas for tumour therapy, highlights the great potential for clinical applications. In addition, a discussion of its limitations and encouraging future directions for its practical clinical application is presented.

The impact of tertiary lymphoid structures on tumor prognosis and the immune microenvironment in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is a common malignancy whose prognosis and treatment outcome are influenced by many factors. Some studies have found that tertiary lymphoid structures (TLSs) in cancer may contribute to prognosis and the prediction of immunotherapy efficacy However, the combined role of TLSs in NSCLC remains unclear. We accessed The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to obtain mRNA sequencing data and clinical information as the TCGA cohort, and used our own sample of 53 advanced NSCLC as a study cohort. The samples were divided into TLS+ and TLS- groups by pathological tissue sections. Patients of the TLS+ group had a better OS (p = 0.022), PFS (p = 0.042), and DSS (p = 0.004) in the TCGA cohort, and the results were confirmed by the study cohort (PFS, p = 0.012). Furthermore, our result showed that the count and size of TLSs are closely associated with the efficacy of immunotherapy. In addition, the TLS+ group was associated with better immune status and lower tumor mutation load. In the tumor microenvironment (TME), the expression levels of CD4+ T cells and CD8+ T cells of different phenotypes were associated with TLSs. Overall, TLSs are a strong predictor of survival and immunotherapeutic efficacy in advanced NSCLC, and T cell-rich TLSs suggest a more ordered and active immune response site, which aids in the decision-making and application of immunotherapy in the clinic.

FPR1, as a Potential Biomarker of Diagnosis and Infliximab Therapy Responses for Crohn's Disease, is Related to Disease Activity, Inflammation and Macrophage Polarization.

Purpose: Crohn's disease (CD) represents a multifaceted inflammatory gastrointestinal condition, with a profound significance placed on unraveling its molecular pathways to enhance both diagnostic capabilities and therapeutic interventions. This study focused on identifying a robust macrophage-related signatures (MacroSig) for diagnosing CD, emphasizing the role of FPR1 in macrophage polarization and its implications in CD. Patients and Methods: Expression profiles from intestinal biopsies and macrophages of 1804 CD patients were retrieved from the Gene Expression Omnibus (GEO). Utilizing CIBERSORTx, differential expression analysis, and weighted correlation network analysis to to identify macrophage-related genes (MRGs). By unsupervised clustering, distinct clusters of CD were identified. Potential biomarkers were identified via using four machine learning algorithms, leading to the establishment of MacroSig which combines insights from 12 machine learning algorithms. Furthermore, the expression of FPR1 was verified in intestinal biopsies of CD patients and two murine experimental colitis models. Finally, we further explored the role of FPR1 in macrophage polarization through single-cell analysis as well as through the study of RAW264.7 cells and peritoneal macrophages. Results: Two distinct clusters with differential levels of macrophage infiltration and inflammation were identified. The MacroSig, which included FPR1 and LILRB2, exhibited high diagnostic accuracy and outperformed existing biomarkers and signatures. Clinical analysis demonstrated a strong correlation of FPR1 with disease activity, endoscopic inflammation status, and response to infliximab treatment. The expression levels of FPR1 were validated in our CD cohort by immunohistochemistry and confirmed in two colitis mouse models. Single-cell analysis indicated that FPR1 is predominantly expressed in macrophages and monocytes. In vitro studies demonstrated that FPR1 was upregulated in M1 macrophages, and its activation promoted M1 polarization. Conclusion: We developed a promising diagnostic signature for CD, and targeting FPR1 to modulate macrophage polarization may represent a novel therapeutic strategy.

Case report: Innovative treatment for one metastatic thyroid-like follicular carcinoma of the kidney with ATM and POLE mutations.

Thyroid-like follicular renal cell carcinoma (TLFRCC), also known as thyroid-like follicular carcinoma of the kidney or thyroid follicular carcinoma like renal tumor, is an exceedingly rare variant of renal cell carcinoma that has only recently been acknowledged. This neoplasm exhibits a distinct follicular morphology resembling that of the thyroid gland. Immunohistochemical analysis reveals positive expression of PAX8, Vimentin, and EMA, while thyroid-specific markers TG and TTF1 are consistently absent. Furthermore, there is a notable absence of any concurrent thyroid pathology on clinical evaluation. Previous reports have suggested that TLFRCC is an indolent, slow-growing malignancy with infrequent metastatic potential. In this report, we present a case of TLFRCC characterized by remarkable ossification and widespread metastasis, including multifocal pulmonary lesions, involvement of the abdominal wall, and infiltration into the psoas muscle. To our knowledge, this represents only the third documented instance of distant metastasis in thyroid follicular renal carcinoma. The current case demonstrates a therapeutic approach that combines radiotherapy with the utilization of toripalimab, a programmed cell death 1 (PD-1) receptor inhibitor, and pazopanib. This treatment regimen was tailored based on comprehensive genomic profiling, which identified mutations in the POLE (catalytic subunit of DNA polymerase epsilon) and ATM (ataxia-telangiectasia mutated) genes, both of which have been implicated in the pathogenesis of various malignant tumors. These findings represent a novel discovery, as such mutations have never been reported in association with TLFRCC. Thus far, this therapeutic approach has proven to be the most efficacious option for treating metastatic TLFRCC among previously reported, and it also marks the first mention of the potential benefits of radiotherapy in managing this particular subtype of renal cell carcinoma.

CIC::NUTM1 sarcomas occurred in soft tissues of upper limbs : a rare case report and literature review.

BACKGROUND: CIC-rearranged sarcomas (CRS) represent a new entity of undifferentiated small round cell sarcoma belonging to the Ewing-like sarcomas family. CRS are the most common type. Fusion partners for the CIC gene include DUX4, FOXO4, and the recently recognizedNUTM1. Rare cases of CIC::NUTM1 sarcoma in pediatric patients have recently been reported in brain, kidney, bone, and soft tissues. However, such cases have not been identified in the soft tissues of the limbs. CASE PRESENTATION: We reported a case of CIC::NUTM1 sarcoma located in the right upper limb of an 18-year-old man. The tumor displayed morphologic features typical of CIC::DUX4 sarcomas, with small- to medium-sized round cells, a lobular pattern, focal spindling, myxoid stroma, and patchy necrosis. The tumor diffusely expressed NUTM1, was positive for WT1cter at weak to moderate intensity, and was focally positive for CD99, while it was negative for keratins, EMA, P40, MyoD1, myogenin, NKX2.2, BCOR, and pan-TRK. Fluorescence in situ hybridization analyses revealed cleavage of the CIC and NUTM1 genes. CONCLUSION: CIC::NUTM1 sarcomas represent a novel molecular variant of CRS with a preference for the central nervous system and younger pediatric persons. Its morphology and phenotype may be mistaken for NUT carcinomas, and the behavior is more progressive than other forms of CRS. For this rare and newly discovered gene fusion variant, it is necessary to integrate molecular and immunohistochemical findings with morphologic features in the diagnosis of undifferentiated neoplasms.

A risk prediction model for delayed bleeding after ESD for gastric precancerous lesions.

OBJECTIVE: To investigate the risk factors for delayed postoperative bleeding after endoscopic submucosal dissection (ESD) in patients with gastric precancerous lesions and to construct a risk prediction model. METHODS: This retrospective analysis included clinical data from patients with gastric precancerous lesions who underwent ESD at Wuhan University People's Hospital between November 2016 and June 2022. An XGBoost model was built to predict delayed bleeding after ESD using risk factors identified by univariable and multivariate logistic regression analysis. The model was evaluated using receiver operating characteristic curves (ROC), and SHapely Additive exPlanations (SHAP) analysis was used to interpret the model. RESULTS: Seven factors were statistically associated with delayed postoperative bleeding in gastric precancerous lesions after ESD: age, low-grade intraepithelial neoplasia, hypertension, lesion size ≥ 40 mm, operative time ≥ 120 min, female, and nonuse of hemoclips. A risk prediction model was established. In the training cohort, the model achieved an AUC of 0.97 (0.96-0.98), a sensitivity of 0.90, a specificity of 0.94, and an F1 score of 0.91. In the validation cohort, the AUC was 0.94(0.90-0.98), with a sensitivity of 0.85, a specificity of 0.89, and an F1 score of 0.85. In the test cohort, the AUC was 0.94 (0.89-0.99), the sensitivity was 0.80, the specificity was 0.92, and the F1 score was 0.84, indicating strong predictive capability. CONCLUSION: In this study, an XGBoost prediction model for assessing the risk of delayed postoperative bleeding after ESD in patients with gastric precancerous lesions was developed and validated. This model can be applied in clinical practice to effectively predict the risk of post-ESD bleeding for individual patients.

Advancements in technology for characterizing the tumor immune microenvironment.

Immunotherapy plays a key role in cancer treatment, however, responses are limited to a small number of patients. The biological basis for the success of immunotherapy is the complex interaction between tumor cells and tumor immune microenvironment (TIME). Historically, research on tumor immune constitution was limited to the analysis of one or two markers, more novel technologies are needed to interpret the complex interactions between tumor cells and TIME. In recent years, major advances have already been made in depicting TIME at a considerably elevated degree of throughput, dimensionality and resolution, allowing dozens of markers to be labeled simultaneously, and analyzing the heterogeneity of tumour-immune infiltrates in detail at the single cell level, depicting the spatial landscape of the entire microenvironment, as well as applying artificial intelligence (AI) to interpret a large amount of complex data from TIME. In this review, we summarized emerging technologies that have made contributions to the field of TIME, and provided prospects for future research.

Deep lymph node enlargement and renal failure caused by hypercalcemia­associated sarcoidosis: A case report.

Sarcoidosis is a rare disease that severely affects the lungs and superficial lymph nodes. In addition, this disease can also affect the skin, eyes and kidneys to varying degrees. The present report described a 32-year-old male patient who was admitted to Renmin Hospital of Wuhan University (Wuhan, China) due to joint pain in the extremities. He was diagnosed with uncorrectable hypercalcemia. A lymph node biopsy revealed the hypercalcemia to be associated with sarcoidosis, with the patient also demonstrating renal failure and lymph node enlargement. Administration of glucocorticoids provided benefits in terms of both primary and recurrent sarcoidosis, which also improved and preserved renal function. After being prescribed with oral prednisone treatment, blood calcium levels returned to normal, which indicated markedly improving renal function. However, the discontinuation of glucocorticoids for 2 months resulted in increased serum calcium and creatinine levels, both of which returned to abnormal levels. Overall, the present case report suggests that clinicians should actively perform sarcoidosis treatment in clinical practice to overcome any unexpected results associated with organ damage.

The proportion of tumour stroma predicts response to treatment of immune checkpoint inhibitor in combination with chemotherapy in patients with stage IIIB-IV non-small cell lung cancer.

AIMS: Immunotherapy has brought a new era to cancer treatment, yet we lack dependable predictors for its effectiveness. This study explores the predictive significance of intratumour stroma proportion (iTSP) for treatment success and prognosis in non-small cell lung cancer (NSCLC) patients undergoing treatment with immune check-point inhibitors (ICIs) together with chemotherapy. METHODS AND RESULTS: We retrospectively collected data from patients with unresectable stage IIIB-IV NSCLC who were treated with first-line ICIs and chemotherapy. Each patient received a confirmed pathological diagnosis, and the pathologist evaluated the iTSP on haematoxylin and eosin (H&E)-stained sections of diagnostic tissue slides. Among the 102 H&E-stained biopsy samples, 61 (59.8%) were categorised as stroma-L (less than 50% iTSP), while 41 (40.2%) were classified as stroma-H (more than 50% iTSP). We observed that the stroma-L group exhibited a significantly better objective response rate (ORR) (72.1 versus 51.2%, P = 0.031) and deeper response depth (DpR) (-50.49 ± 28.79% versus -35.83 ± 29.91%, P = 0.015) compared to the stroma-H group. Furthermore, the stroma-L group showed longer median progression-free survival (PFS) (9.6 versus 6.0 months, P = 0.011) and overall survival (OS) (24.0 versus 12.2 months, P = 0.001) compared to the stroma-H group. Multivariate Cox proportional hazards regression analysis indicated that iTSP was a highly significant prognostic factor for both PFS [hazard ratio (HR) = 1.713; P = 0.030] and OS (HR = 2.225; P = 0.003). CONCLUSION: Our findings indicate that a lower iTSP corresponds to improved clinical outcomes and greater DpR in individuals with stage IIIB-IV NSCLC treated with first-line ICIs and chemotherapy. The iTSP could potentially serve as a predictive biomarker for ICIs therapy response.

circLIFR-007 reduces liver metastasis via promoting hnRNPA1 nuclear export and YAP phosphorylation in breast cancer.

Cancer metastasis is the major cause of death in patients with breast cancer (BC). The liver is a common site of breast cancer metastasis, and the 5-year survival rate of patients with breast cancer liver metastases (BCLMs) is only about 8.5 %. CircRNAs are involved in a variety of cancer-related pathological behaviors, and their unique structure and resistance to RNA degradation enable them to serve as ideal diagnostic biomarkers and therapeutic targets. Therefore, it is important to investigate the role and molecular mechanism of circRNAs in cancer metastasis. CircLIFR-007 was identified as a critical circular RNA in BC metastasis by circRNAs microarray and qRT-PCR experiment. Cell function assays were performed to explore the effect of circLIFR-007 in breast cancer cells. Experiments in vivo validated the function of circLIFR-007. Several molecular assays were performed to investigate the underlying mechanisms. We found that circLIFR-007 acted as a negative controller in breast cancer liver metastasis. CircLIFR-007 upregulates the phosphorylation level of YAP by exporting hnRNPA1 to promote the combination between hnRNPA1 and YAP in the cytoplasm. Overexpression of circLIFR-007 suppressed the expression of liver metastasis-related proteins, SREBF1 and SNAI1, which were regulated by transcription factor YAP. Functionally, circLIFR-007 inhibits the proliferation and metastasis of breast cancer cells both in vivo and in vitro.

Colorectal cancer histopathology image analysis: A comparative study of prognostic values of automatically extracted morphometric nuclear features in multispectral and red-blue-green imagery.

OBJECTIVES: Multispectral imaging (MSI) has been utilized to predict the prognosis of colorectal cancer (CRC) patients, however, our understanding of the prognostic value of nuclear morphological parameters of bright-field MSI in CRC is still limited. This study was designed to compare the efficiency of MSI and standard red-green-blue (RGB) images in predicting the prognosis of CRC. METHODS: We compared the efficiency of MS and conventional RGB images on the quantitative assessment of hematoxylin-eosin (HE) stained histopathology images. A pipeline was developed using a pixel-wise support vector machine (SVM) classifier for gland-stroma segmentation, and a marker-controlled watershed algorithm was used for nuclei segmentation. The correlation between extracted morphological parameters and the five-year disease-free survival (5-DFS) was analyzed. RESULTS: Forty-seven nuclear morphological parameters were extracted in total. Based on Kaplan-Meier analysis, eight features derived from MS images and seven featured derived from RGB images were significantly associated with 5-DFS, respectively. Compared with RGB images, MSI showed higher accuracy, precision, and Dice index in nuclei segmentation. Multivariate analysis indicated that both integrated parameters 1 (factors negatively correlated with CRC prognosis including nuclear number, circularity, eccentricity, major axis length) and 2 (factors positively correlated with CRC prognosis including nuclear average area, area perimeter, total area/total perimeter ratio, average area/perimeter ratio) in MS images were independent prognostic factors of 5-DFS, in contrast with only integrated parameter 1 (P<0.001) in RGB images. More importantly, the quantification of HE-stained MS images displayed higher accuracy in predicting 5-DFS compared with RGB images (76.9% vs 70.9%). CONCLUSIONS: Quantitative evaluation of HE-stained MS images could yield more information and better predictive performance for CRC prognosis than conventional RGB images, thereby contributing to precision oncology.

Methylation of GPRC5A promotes liver metastasis and docetaxel resistance through activating mTOR signaling pathway in triple negative breast cancer.

AIMS: This study aims to explore the function and mechanism of G Protein-coupled receptor class C group 5 member A (GPRC5A) in docetaxel-resistance and liver metastasis of breast cancer. METHODS: Single-cell RNA transcriptomic analysis and bioinformatic analysis are used to screen relevant genes in breast cancer metastatic hepatic specimens. MeRIP, dual-luciferase analysis and bioinformation were used to detect m6A modulation. Mass spectrometry (MS), co-inmunoprecipitation (co-IP) and immunofluorescence colocalization were executed to explore the mechanism of GPRC5A in breast cancer cells. RESULT: GPRC5A was upregulated in triple-negative breast cancer (TNBC) and was associated with a poor prognosis. In vitro and in vivo experiments demonstrated that knockdown of GPRC5A alleviated metastasis and resistance to docetaxel in TNBC. Overexpression of GPRC5A had the opposite effects. The m6A methylation of GPRC5A mRNA was modulated by METTL3 and YTHDF1, which facilitates its translation. GPRC5A inhibited the ubiquitination-dependent degradation of LAMTOR1, resulting in the recruitment of mTORC1 to lysosomes and activating the mTORC1/p70s6k signaling pathway. CONCLUSION: METTL3/YTHDF1 axis up-regulates GPRC5A expression by m6A methylation. GPRC5A activates mTORC1/p70s6k signaling pathway by recruiting mTORC1 to lysosomes, consequently promotes docetaxel-resistance and liver metastasis.

Expert Consensus on the Diagnosis and Treatment of NRG1/2 Gene Fusion Solid Tumors.

The fusion genes NRG1 and NRG2 , members of the epidermal growth factor (EGF) receptor family, have emerged as key drivers in cancer. Upon fusion, NRG1 retains its EGF-like active domain, binds to the ERBB ligand family, and triggers intracellular signaling cascades, promoting uncontrolled cell proliferation. The incidence of NRG1 gene fusion varies across cancer types, with lung cancer being the most prevalent at 0.19 to 0.27%. CD74 and SLC3A2 are the most frequently observed fusion partners. RNA-based next-generation sequencing is the primary method for detecting NRG1 and NRG2 gene fusions, whereas pERBB3 immunohistochemistry can serve as a rapid prescreening tool for identifying NRG1 -positive patients. Currently, there are no approved targeted drugs for NRG1 and NRG2 . Common treatment approaches involve pan-ERBB inhibitors, small molecule inhibitors targeting ERBB2 or ERBB3, and monoclonal antibodies. Given the current landscape of NRG1 and NRG2 in solid tumors, a consensus among diagnostic and treatment experts is proposed, and clinical trials hold promise for benefiting more patients with NRG1 and NRG2 gene fusion solid tumors.

Demethylase FTO-Mediated m6A Modification of lncRNA MEG3 Activates Neuronal Pyroptosis via NLRP3 Signaling in Cerebral Ischemic Stroke.

Neuronal death following ischemia is the primary cause of death and disability in patients with ischemic stroke. N6-methyladenosine (m6A) modification plays essential role in various physiological and pathological conditions, but its role and mechanism in ischemic neuronal death remain unclear. In the present study, neuronal pyroptosis was an important event in brain injury caused by ischemic stroke, and the upregulation of long non-coding RNA (lncRNA) maternally expressed gene 3 (MEG3) following cerebral ischemia was a key factor in activating ischemic neuronal pyroptosis via NLRP3/caspase-1/GSDMD signaling. Moreover, we first demonstrated that the demethylase fat mass and obesity-associated protein (FTO), which was decreased following ischemia, regulated MEG3 expression in an m6A-dependent manner by affecting its stability, thereby activating neuronal pyroptosis via NLRP3/caspase-1/GSDMD signaling, and ultimately leading to ischemic brain damage. Therefore, the present study provides new insights for the mechanism of ischemic stroke, and suggests that FTO may be a potential therapeutic target for ischemic stroke.

Primary acinic cell carcinoma of the breast: A case report and literature review.

Acinic cell carcinoma (ACCA), a type of malignant epithelial neoplasm, tends to occur in the parotid gland, and is occasionally found within the breast. Published literature regarding primary ACCA of the breast is scarce, and the number of reports may be fewer than 100. At present, full clinical details have not been published. As an extremely rare disorder, ACCA cannot be definitively diagnosed depending on microscopic structure alone and often requires the assistance of immunohistochemistry. Currently, universal therapies are not available. Here, we present a 47-year-old patient with a history of a palpable mass in the outer upper quadrant of the left breast for more than 2 years, which had obviously increased in size in the last half year. This patient was definitively diagnosed with primary ACCA of the breast. Neoadjuvant chemotherapy was performed preoperatively, and drug sensitivity tests based on primary tumor cells were conducted after surgery and successfully screened chemotherapy schemes for the patient's greater benefit. The whole treatment course followed the guidelines for invasive breast cancer. The patient was free of symptoms for 14 months after surgery. Long-term follow-up is in progress. Altogether, to further broaden the understanding of primary ACCA of the breast, we detail the diagnosis and treatment of one patient and review the relevant literature.

Expert consensus on the diagnosis and treatment of RET gene fusion non-small cell lung cancer in China.

The rearranged during transfection (RET) gene is one of the receptor tyrosine kinases and cell-surface molecules responsible for transmitting signals that regulate cell growth and differentiation. In non-small cell lung cancer (NSCLC), RET fusion is a rare driver gene alteration associated with a poor prognosis. Fortunately, two selective RET inhibitors (sRETi), namely pralsetinib and selpercatinib, have been approved for treating RET fusion NSCLC due to their remarkable efficacy and safety profiles. These inhibitors have shown the ability to overcome resistance to multikinase inhibitors (MKIs). Furthermore, ongoing clinical trials are investigating several second-generation sRETis that are specifically designed to target solvent front mutations, which pose a challenge for first-generation sRETis. The effective screening of patients is the first crucial step in the clinical application of RET-targeted therapy. Currently, four methods are widely used for detecting gene rearrangements: next-generation sequencing (NGS), reverse transcription-polymerase chain reaction (RT-PCR), fluorescence in situ hybridization (FISH), and immunohistochemistry (IHC). Each of these methods has its advantages and limitations. To streamline the clinical workflow and improve diagnostic and treatment strategies for RET fusion NSCLC, our expert group has reached a consensus. Our objective is to maximize the clinical benefit for patients and promote standardized approaches to RET fusion screening and therapy.

Integrative multi-omics analyses unravel the immunological implication and prognostic significance of CXCL12 in breast cancer.

Background: CXCL12 is a vital factor in physiological and pathological processes, by inducing migration of multiple cells. We aimed to comprehensively detect the role of CXCL12 in breast cancer, and explore novel CXCL12-related biomarkers through integrative multi-omics analyses to build a powerful prognostic model for breast cancer patients. Methods: Immunohistochemistry analysis of the tissue microarray was performed to evaluate the correlation between CXCL12 expression levels and breast cancer patient outcomes. Combined single-nucleus and spatial transcriptomics data was used to uncover the expression distribution of CXCL12 in breast cancer microenvironment. CXCL12-related genes were identified by WGCNA analysis. Univariate Cox and LASSO regression analyses were then conducted to screen prognostic genes from above CXCL12-related genes, followed by the construction of the CXCL12-related prognostic signature, identification of risk groups, and external validation of the prognostic signature. Analyses of biological function, mutation landscape, immune checkpoint genes and immune cells, were performed to further reveal the differences between high/low-risk groups. Paired single-cell RNA-seq and bulk RNA-seq were analyzed to further disclose the association between the risk score and the complex tumor immune microenvironment. To screen potential therapeutic agents for breast cancer patients, analyses of gene-drug correlation and sensitivity to immunotherapy were conducted. Results: High expression of CXCL12 was linked with a prolonged survival in breast cancer. A total of 402 genes were identified by WGCNA analysis and 11 genes, covering VAT1L, TMEM92, SDC1, RORB, PCSK9, NRN1, NACAD, JPH3, GJA1, BMP8B and ADAMTS2, were screened as the candidate prognostic genes. Next, the prognostic signature was built and validated using these genes to predict the outcomes of breast cancers. The high-risk group patients exhibited significantly inferior prognoses. The combination of the risk score and tumor mutational burden (TMB) had remarkably improved performance in predicting patient outcomes. Besides, high-risk group patients showed higher infiltration of M2-like macrophages. Finally, several potential anticancer drugs were identified. The high-risk group patients were more sensitive to immunotherapy but resistant to docetaxel. Conclusions: CXCL12 has important immunological implication and prognostic significance in breast cancer. The CXCL12-related prognostic model could well predict the prognosis and treatment response of breast cancers.