Comprehensive analysis of the cancer driver genes in breast cancer demonstrates their roles in cancer prognosis and tumor microenvironment

Unmutated RRAS2 emerges as a key oncogene in post-partum-associated triple negative breast cancer

BACKGROUND

Breast cancer (BC) is the most common cancer in women, with triple negative BC (TNBC) accounting for 20% of cases. While early detection and targeted therapies have improved overall life expectancy, TNBC remains resistant to current treatments. Although parity reduces the lifetime risk of developing BC, pregnancy increases the risk of developing TNBC for years after childbirth. Although numerous gene mutations have been associated with BC, no single gene alteration has been identified as a universal driver. RRAS2 is a RAS-related GTPase rarely found mutated in cancer.

METHODS

Conditional knock-in mice were generated to overexpress wild type human RRAS2 in mammary epithelial cells. A human sample cohort was analyzed by RT-qPCR to measure RRAS2 transcriptional expression and to determine the frequency of both a single-nucleotide polymorphism (SNP rs8570) in the 3'UTR region of RRAS2 and of genomic DNA amplification in tumoral and non-tumoral human BC samples.

RESULTS

Here we show that overexpression of wild-type RRAS2 in mice is sufficient to develop TNBC in 100% of females in a pregnancy-dependent manner. In human BC, wild-type RRAS2 is overexpressed in 68% of tumors across grade, location, and molecular type, surpassing the prevalence of any previously implicated alteration. Still, RRAS2 overexpression is notably higher and more frequent in TNBC and young parous patients. The increased prevalence of the alternate C allele at the SNP position in tumor samples, along with frequent RRAS2 gene amplification in both tumors and blood of BC patients, suggests a cause-and-effect relationship between RRAS2 overexpression and breast cancer.

CONCLUSIONS

Higher than normal expression of RRAS2 not bearing activating mutations is a key driver in the majority of breast cancers, especially those of the triple-negative type and those linked to pregnancy.

Dkk1 as a Prognostic Marker for Neoadjuvant Chemotherapy Response in Breast Cancer Patients

PURPOSE

To investigate the role of Dkk1 as a predictor of response to NACT in BC patients.

METHODS

This retrospective monocentric study included 145 women who had undergone NACT followed by breast surgery. Dkk1 protein expression was assessed using immunohistochemistry staining in core needle biopsies and mammary carcinoma specimens.

RESULTS

Dkk1 levels were lower in treated BC tumours than in untreated tumours. The outcomes of 68 matched pre- and post-therapy tissues showed that Dkk1 levels in mammary carcinoma tissues were significantly predicted by levels in core needle biopsies and that Dkk1 expression was reduced in 83% of cases. Smaller cT stage, positive Her2 expression, and decreased Dkk1-IRS in core needle biopsy tissues were all independent predictors of regression grade (R4), according to Sinn. However, the percentage of Dkk1 expression differences prior to and following NACT had no effect on PFS or OS.

CONCLUSIONS

In this study, we demonstrated for the first time that Dkk1 could be identified as an independent predictor of NACT response in BC patients, particularly those with TNBC. Further research with a multicentric expanded (pre-/post-therapy) sample set and better-defined populations in terms of molecular subtypes, therapy modality, and long-term follow-up is recommended to obtain more solid evidence.

Preparation and application of patient-derived xenograft mice model of colorectal cancer

Objectives

Patient-derived xenograft (PDX) model becomes a more and more important tool for tumor research. This study aimed to establish a colorectal cancer PDX model and verify its applicability.

Materials and Methods

Fresh human colorectal cancer tissue was surgically removed and subcutaneously inoculated into immunodeficient mice to establish the PDX model. Hematoxylin and eosin (HE) staining and immunohistochemical staining were used to evaluate the model. The successful PDX model was selected to study the efficacy of capecitabine in treating colorectal cancer.

Results

HE staining showed that the PDX mice model of colorectal cancer could preserve the histological characteristics of the primary tumor. Immunohistochemistry staining showed α-fetoprotein (AFP), carcinoembryonic antigen (CEA), and E-cadherin were strongly positively expressed in primary human and PDX tumor tissues, with a high degree of similarity. Capecitabine significantly inhibited PDX tumor growth and reduced the expression of AFP and CEA proteins in the tumor tissues (all P s<0.05).

Conclusion

We successfully established a colorectal cancer PDX model, and the PDX model could retain the histological and biological characteristics of the primary tumor. Using this PDX model, we revealed that capecitabine at a dose of 300-400 mg/kg can effectively treat colorectal cancer, and no significant difference in toxicity was found among different dose groups. The current work provides a feasible framework for establishing and validating the PDX tumor model to better facilitate the evaluation of drug efficacy and safety.

Machine learning identification of cuproptosis and necroptosis-associated molecular subtypes to aid in prognosis assessment and immunotherapy response prediction in low-grade glioma

Both cuproptosis and necroptosis are typical cell death processes that serve essential regulatory roles in the onset and progression of malignancies, including low-grade glioma (LGG). Nonetheless, there remains a paucity of research on cuproptosis and necroptosis-related gene (CNRG) prognostic signature in patients with LGG. We acquired patient data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) and captured CNRGs from the well-recognized literature. Firstly, we comprehensively summarized the pan-cancer landscape of CNRGs from the perspective of expression traits, prognostic values, mutation profiles, and pathway regulation. Then, we devised a technique for predicting the clinical efficacy of immunotherapy for LGG patients. Non-negative matrix factorization (NMF) defined by CNRGs with prognostic values was performed to generate molecular subtypes (i.e., C1 and C2). C1 subtype is characterized by poor prognosis in terms of disease-specific survival (DSS), progression-free survival (PFS), and overall survival (OS), more patients with G3 and tumour recurrence, high abundance of immunocyte infiltration, high expression of immune checkpoints, and poor response to immunotherapy. LASSO-SVM-random Forest analysis was performed to aid in developing a novel and robust CNRG-based prognostic signature. LGG patients in the TCGA and GEO databases were categorized into the training and test cohorts, respectively. A five-gene signature, including SQSTM1, ZBP1, PLK1, CFLAR, and FADD, for predicting OS of LGG patients was constructed and its predictive reliability was confirmed in both training and test cohorts. In both the training and the test datasets (cohorts), higher risk scores were linked to a lower OS rate. The time-dependent ROC curve proved that the risk score had outstanding prediction efficiency for LGG patients in the training and test cohorts. Univariate and multivariate Cox regression analyses showed the CNRG-based prognostic signature independently functioned as a risk factor for OS in LGG patients. Furthermore, we developed a highly reliable nomogram to facilitate the clinical practice of the CNRG-based prognostic signature (AUC > 0.9). Collectively, our results gave a promising understanding of cuproptosis and necroptosis in LGG, as well as a tailored prediction tool for prognosis and immunotherapeutic responses in patients.

Biodegradation of Low-Density Polyethylene—LDPE by the Lepidopteran Galleria Mellonella Reusing Beekeeping Waste

Plastic pollution is one of the most serious environmental problems of this century because most plastics are single-use, and once their useful life is over, they become pollutants, since their decomposition takes approximately 100–400 years. The objective of this research is to evaluate the efficacy of low-density polyethylene (LDPE) biodegradation by G. mellonella in the district of Pangoa, Junín, Peru. For the development of the study, the G. mellonella was conditioned in three groups of beekeeping residues (beeswax, balanced diet, and wheat bran); after the conditioning stage, the biodegradation treatment was developed, which consisted of placing the G. mellonella in terrariums with the LDPE, the treatments were carried out at three different times (24, 36, and 48 h). To evaluate the efficacy of biodegradation, two analyses were taken into account: the Raman analysis of the low-density polyethylene samples and the weight reduction of the treated LDPE. The results of the Raman analysis indicated that the best treatment was the one applied with G. mellonella conditioned with beeswax, obtaining a wavelength intensity of 0.45 μ.a., while the weight reduction of the LDPE indicated that the best results were given at 36 h and conditioned with beeswax with a reduction of 236.3 mg. In conclusion, the use of G. mellonella for the biodegradation of low-density polyethylene is effective when it is conditioned with beeswax and the treatment is carried out at 36 h.

The potential effects and mechanisms of breast inflammatory lesions on the occurrence and development of breast cancer

Breast cancer as the most common cancer in women has become the leading cause of cancer death for women. Although many inflammatory factors increase the risk of breast cancer, there are very few studies on the mechanisms by which inflammation affects the initiation and progression of breast cancer. Here, we profiled and compared the transcriptome of normal tissues, inflammatory breast tissues, benign breast tumors, and malignant breast tumors. To find key regulatory factors, a protein interaction network between characteristic modules in inflammatory lesions and ER-negative (ER⁻) breast cancer was constructed and inflammation-cancer interface genes were identified. We found that the transcriptional profile of inflammatory breast tissues was similar with ER⁻ malignant tumors, featured with low ER expression levels and similar immune signaling pathway activation. Through comprehensive protein network analysis, we identified the interface genes and chemokine signaling pathway that have the potential to promote inflammatory cancer transformation. These interface genes could be used as a risk factor to provide a certain basis for the clinical early detection and treatment of breast cancer. This is the first study to explore the association between breast inflammatory lesions and breast cancer at the transcriptome level. Our inflammation data and research results provide a basis for future inflammation-cancer transformation analysis.

Overexpressed VDAC1 in breast cancer as a novel prognostic biomarker and correlates with immune infiltrates

BACKGROUND

More and more evidence suggests that cancer is a mitochondrial metabolic disease recently and mitochondria dysfunction is critical to tumorigenesis. As a gatekeeper of mitochondria, the voltage-dependent anion channel 1 (VDAC1) is associated with the development of breast cancer (BC). However, its potential mechanism and clinical significance remain unclear; thus, in this research, we aimed to explore it.

METHODS

VDAC1 expression in BC tissues and normal tissues was obtained from The Cancer Genome Atlas (TCGA) and validated by datasets from the gene expression omnibus (GEO) database. Then, the relationships between VDAC1 expression and clinicopathological features were analyzed. Receiver operating characteristics (ROC) curves were used to identify the diagnostic value of VDAC1. The prognostic value was evaluated by Kaplan-Meier survival curves and Cox regression analysis. VDAC1 with its co-expression genes were subjected to enrichment analysis to explore potential mechanisms in BC and the protein-protein interaction (PPI) network was constructed. At last, the association between VDAC1 expression and infiltration levels of immune cell infiltration by various methods, as well as their corresponding markers, was analyzed. We also analyzed the correction between VDAC1 expression and eight immune checkpoint genes and the tumor immune dysfunction and exclusion (TIDE) scores of each BC sample in TCGA were calculated and the differences between high and low VDAC1 expression groups were analyzed.

RESULTS

VDAC1 expression was remarkably elevated in BC (p < 0.001), and high expression of VDAC1 was associated with the positive expression of ER (p = 0.004), PR (p = 0.033), and HER2 (p = 0.001). ROC analysis suggested that VDAC1 had diagnosed value in BC. The Kaplan-Meier analysis suggested that higher expression of VDAC1 was associated with shorter overall survival (OS), and further Cox regression analysis revealed that VDAC1 was an independent factor of unfavorable prognosis in BC patients. Enrichment analysis of VDAC1 and its co-expression suggested that VDAC1 was related to the regulation of mitochondrial energy metabolism and protein modification, and the HIF-1 singing pathway might be the potential mechanism in BC. Notably, we found that VDAC1 expression was infiltration levels of most types of immune cells, as well as the expression of marker genes of immune cells. The ICGs PDCD1, CTLA4, LAG3, SIGLEC15, and TIGIT were negatively corrected with VDAC1 expression in BC. TIDE scores between the low and high expression groups showed no difference.

CONCLUSION

Overexpressed VDAC1 in BC could be severed as a novel biomarker for diagnosis and VDAC1 was an independent factor for adverse prognosis prediction. Our study revealed that VDAC1 might inhibit tumor immunity and might be a novel therapeutic target in BC.

Differences in tumor-infiltrating lymphocyte density and prognostic factors for breast cancer by patient age

Background

Lymphocytes that surround cancer participate in tumor-related immune responses and are called tumor-infiltrating lymphocytes (TILs). Several recent reports suggest TILs index the tumor microenvironment and predict the therapeutic effect of chemotherapy. However, only few studies have studied the relationship between age and TILs. Aging reduces host immunity, and we predict that it may also affect TILs. Thus, we hypothesized that older breast cancer (BC) patients may have low TIL density than younger BC patients. Here, we retrospectively analyzed the differences in TILs by age and the therapeutic effects of preoperative chemotherapy (POC) in BC patients who were aged either less than 45 years or more than 60 years.

Methods

We retrospectively examined the data of 356 breast cancer patients who underwent POC, including 75 patients aged ≤ 45 years and 116 patients aged > 60 years. Using pre-treatment needle biopsy specimens, TIL density was compared for each age group by Student’s t-test. After analyzing different factors that affect TIL density, prognostic factors were also examined.

Results

Older patients with triple-negative BC had significantly lower TIL density than younger patients, while in human epidermal growth factor receptor 2 (HER2)-enriched BC, TIL density was significantly higher in the younger age group than that in the older age group. In addition, younger patients with HER2-rich breast cancer showed significantly higher complete pathological response rates than older patients with HER2-rich BC. In addition, significant differences in overall survival were observed among these patients with triple-negative BC.

Conclusions

Our study suggests that younger BC patients possess significantly higher TIL density than older patients. These differences may influence the therapeutic efficacy in highly immunogenic subtypes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02513-5.