New MYC IHC Classifier Integrating Quantitative Architecture Parameters to Predict MYC Gene Translocation in Diffuse Large B-Cell Lymphoma

A digital method to interpret the C-MYC stain in diffuse large B cell lymphoma

Diffuse large B-cell lymphoma, not otherwise specified (DLBCL, NOS) is a heterogenous group of aggressive lymphomas. C-MYC expression by immunohistochemical stain (IHC) is shown to be an independent prognostic factor in DLBCL. In the clinical setting, MYC stain is currently evaluated by manual quantification with a minimum positivity cut-off 40%. Manual quantification methods can be subjective and may show intra- and interobserver variability and variability between centers. Thus, stains which require definitive quantification such as MYC needs better standardized and precise methods. Here we present a simple digital algorithm for quantitative evaluation of MYC stain in DLBCL, NOS. For this, slides immunostained for C-MYC were scanned at 40X with a high-resolution, Philips Ultra Fast scanner (Koninklijke Philips N.V. Cambridge, MA). The images were manually assessed and appropriate areas with neoplastic cells were selected. For quantification, positive and negative C-MYC staining nuclei were scored using a modified Visiopharm APP Nuclei Detection, AI (Brightfield) using Visiopharm Image Analysis software (Visiopharm, Hørsholm, Denmark version 2018.09). The percentage positivity resulted by the digital method was concordant with the pathologist’s interpretation with statistical significance (rs: 0.85968; p (2-tailed) = 0). Minor disadvantages were observed including failure to detect very weak staining and inability to separate neoplastic and non-neoplastic nuclei when admixed in the same area. If combined with a quick manual evaluation, a digital method like this with precision and reproducibility will be of great use in quantitative evaluation of MYC and other similar stains in clinical setting and will reduce intra- and interobserver variability.

Single-cell sequencing reveals MYC targeting gene MAD2L1 is associated with prostate cancer bone metastasis tumor dormancy

Background

Among malignant tumors, bone metastasis is frequently associated with prostate cancer which is seen in about 80% of patients. During cancer treatments, some tumor cells switch to a "dormant mode" to help tumor cells avoid attack from the immune system and anti-tumor therapies. In this dormant mode, tumor cells can be resuscitated, causing cancer to reoccur. The generally accepted explanation for this phenomenon is that the tumor cells have spread to the bone marrow before treatment and are dormant in the bone marrow. However, the key mechanism for inducing and maintaining the dormancy of these prostate cancer disseminated tumor cells in the bone marrow is still unclear. Therefore, studying the dormancy mechanism of tumor cells in bone metastasis is of great significance for the treatment and the prevention of recurrence of prostate cancer.

Methods

We obtained single-cell RNA-seq data of tumors from mouse models of prostate cancer bone metastasis mouse model numbered (GSE147150) from the GEO database, and obtained RNA-seq expression data and clinical information from The Cancer Genome Atlas Program (TCGA) of prostate cancer patients from the USCS Xena database. Screening of differential genes and annotation of GO functions were performed separately. Subsequently, the screened differential genes were compared and analyzed with 50 classic Hallmark signaling pathways, and the prognosis analysis of prostate cancer patients in TCGA data was performed to discover the key genes of the dormant mechanism of tumor cells in bone metastasis, and obtain new biomarkers that can be used to predict the prognosis of patients.

Results

A total of 378 differentially expressed genes were screened, of which 293 were significantly up-regulated and 85 were significantly down-regulated. Among them, the up-regulated genes were mainly related to the immune response, and the down-regulated genes were mainly related to the cell cycle. Through GSVA (Gene set variation analysis), it is found that there are differences in a total of 3 signal pathways: COMPLEMENT, MYC_TARGETS_V1 and MYC_TARGETS_V2. By comparing and analyzing the significantly down-regulated genes in dormant tumor cells with MYC_TARGETS_V1, MYC_TARGETS_V2, three significantly down-regulated genes were obtained: Ccna2, Mad2L1 and Plk1.

Conclusion

In summary, our findings indicate that the MYC targeting gene Mad2L1 is potentially related to the dormancy mechanism of prostate cancer. At the same time, Mad2L1, a gene associated with dormant prostate cancer cells, may be used as a biomarker for prognostic survival.

High Myc expression and transcription activity underlies intra-tumoral heterogeneity in triple-negative breast cancer

We have previously identified a novel intra-tumoral dichotomy in triple-negative breast cancer (TNBC) based on the differential responsiveness to a reporter containing the Sox2 regulatory region-2 (SRR2), with reporter responsive (RR) cells being more stem-like than reporter unresponsive (RU) cells. Using bioinformatics, we profiled the protein-DNA binding motifs of SRR2 and identified Myc as one of the potential transcription factors driving SRR2 activity. In support of its role, Myc was found to be highly expressed in RR cells as compared to RU cells. Enforced expression of MYC in RU cells resulted in a significant increase in SRR2 activity, Myc-DNA binding, proportion of cellsexpressing CD44+/CD24-, chemoresistance and mammosphere formation. Knockdown of Myc using siRNA in RR cells led to the opposite effects. We also found evidence that the relatively high ERK activation in RR cells contributes to their high expression of Myc and stem-like features. Using confocal microscopy and patient samples, we found a co-localization between Myc and CD44 in the same cell population. Lastly, a high proportion of Myc-positive cells in tumors significantly correlated with a short patient survival. In conclusion, inhibition of the MAPK/ERK/Myc axis may be an effective approach in eliminating stem-like cells in TNBC.