The clinical significance of adenomatous polyposis coli (APC) and catenin Beta 1 (CTNNB1) genetic aberrations in patients with melanoma.

BACKGROUND: Melanoma-intrinsic activated ß-catenin pathway, the product of the catenin beta 1 (CTNNB1) gene, has been associated with low/absent tumor-infiltrating lymphocytes, accelerated tumor growth, metastases development, and resistance to anti-PD-L1/anti-CTLA-4 agents in mouse melanoma models. Little is known about the association between the adenomatous polyposis coli (APC) and CTNNB1 gene mutations in stage IV melanoma with immunotherapy response and overall survival (OS). METHODS: We examined the prognostic significance of somatic APC/CTNNB1 mutations in the Cancer Genome Atlas Project for Skin Cutaneous Melanoma (TCGA-SKCM) database. We assessed APC/CTNNB1 mutations as predictors of response to immunotherapies in a clinicopathologically annotated metastatic patient cohort from three US melanoma centers. RESULTS: In the TCGA-SKCM patient cohort (n = 434) presence of a somatic APC/CTNNB1 mutation was associated with a worse outcome only in stage IV melanoma (n = 82, median OS of APC/CTNNB1 mutants vs. wild-type was 8.15 vs. 22.8 months; log-rank hazard ratio 4.20, p = 0.011). APC/CTNNB1 mutation did not significantly affect lymphocyte distribution and density. In the 3-melanoma institution cohort, tumor tissues underwent targeted panel sequencing using two standards of care assays. We identified 55 patients with stage IV melanoma and APC/CTNNB1 genetic aberrations (mut) and 169 patients without (wt). At a median follow-up of more than 25 months for both groups, mut compared with wt patients had slightly more frequent (44% vs. 39%) and earlier (66% vs. 45% within six months from original diagnosis of stage IV melanoma) development of brain metastases. Nevertheless, time-to-development of brain metastases was not significantly different between the two groups. Fortunately, mut patients had similar clinical benefits from PD-1 inhibitor-based treatments compared to wt patients (median OS 26.1 months vs. 29.9 months, respectively, log-rank p = 0.23). Less frequent mutations in the NF1, RAC1, and PTEN genes were seen in the mut compared with wt patients from the 3-melanoma institution cohort. Analysis of brain melanoma tumor tissues from a separate craniotomy patient cohort (n = 55) showed that melanoma-specific, activated ß-catenin (i.e., nuclear localization) was infrequent (n = 3, 6%) and not prognostic in established brain metastases. CONCLUSIONS: APC/CTNNB1 mutations are associated with a worse outcome in stage IV melanoma and early brain metastases independent of tumor-infiltrating lymphocyte density. However, PD1 inhibitor-based treatments provide comparable benefits to both mut and wt patients with stage IV melanoma.

Analysis of mRNA Dynamics Using RNA Sequencing Data.

The RNA abundance of each gene is determined by its rates of transcription and RNA decay. Biochemical experiments that measure these rates, including transcription inhibition and metabolic labelling, are challenging to perform and are largely limited to in vitro settings. Most transcriptomic studies have focused on analyzing changes in RNA abundances without attributing those changes to transcriptional or posttranscriptional regulation. Estimating differential transcription and decay rates of RNA molecules would enable the identification of regulatory factors, such as transcription factors, RNA binding proteins, and microRNAs, that govern large-scale shifts in RNA expression. Here, we describe a protocol for estimating differential stability of RNA molecules between conditions using standard RNA-sequencing data, without the need for transcription inhibition or metabolic labeling. We apply this protocol to in vivo RNA-seq data from individuals with Alzheimer's disease and demonstrate how estimates of differential stability can be leveraged to infer the regulatory factors underlying them.

Pan-cancer analysis of mRNA stability for decoding tumour post-transcriptional programs.

Measuring mRNA decay in tumours is a prohibitive challenge, limiting our ability to map the post-transcriptional programs of cancer. Here, using a statistical framework to decouple transcriptional and post-transcriptional effects in RNA-seq data, we uncover the mRNA stability changes that accompany tumour development and progression. Analysis of 7760 samples across 18 cancer types suggests that mRNA stability changes are ~30% as frequent as transcriptional events, highlighting their widespread role in shaping the tumour transcriptome. Dysregulation of programs associated with >80 RNA-binding proteins (RBPs) and microRNAs (miRNAs) drive these changes, including multi-cancer inactivation of RBFOX and miR-29 families. Phenotypic activation or inhibition of RBFOX1 highlights its role in calcium signaling dysregulation, while modulation of miR-29 shows its impact on extracellular matrix organization and stemness genes. Overall, our study underlines the integral role of mRNA stability in shaping the cancer transcriptome, and provides a resource for systematic interrogation of cancer-associated stability pathways.

Melanomas with concurrent BRAF non-p.V600 and NF1 loss-of-function mutations are targetable by BRAF/MEK inhibitor combination therapy.

Although combination BRAF/MEK inhibition has produced significant survival benefits for BRAF p.V600 mutant melanomas, targeted therapies approved for BRAF non-p.V600 mutant melanomas remain limited. Through the analysis of 772 cutaneous melanoma exomes, we reveal that BRAF non-p.V600 mutations co-occurs more frequently with NF1 loss, but not with oncogenic NRAS mutations, than expected by chance. We present cell signaling data, which demonstrate that BRAF non-p.V600 mutants can signal as monomers and dimers within an NF1 loss context. Concordantly, BRAF inhibitors that inhibit both monomeric and dimeric BRAF synergize with MEK inhibition to significantly reduce cell viability in vitro and tumor growth in vivo in BRAF non-p.V600 mutant melanomas with co-occurring NF1 loss-of-function mutations. Our data suggest that patients harboring BRAF non-p.V600 mutant melanomas may benefit from current FDA-approved BRAF/MEK inhibitor combination therapy currently reserved for BRAF p.V600 mutant patients.

A nuclear cAMP microdomain suppresses tumor growth by Hippo pathway inactivation.

Cyclic AMP (cAMP) signaling is localized to multiple spatially distinct microdomains, but the role of cAMP microdomains in cancer cell biology is poorly understood. Here, we present a tunable genetic system that allows us to activate cAMP signaling in specific microdomains. We uncover a nuclear cAMP microdomain that activates a tumor-suppressive pathway in a broad range of cancers by inhibiting YAP, a key effector protein of the Hippo pathway, inside the nucleus. We show that nuclear cAMP induces a LATS-dependent pathway leading to phosphorylation of nuclear YAP solely at serine 397 and export of YAP from the nucleus with no change in YAP protein stability. Thus, nuclear cAMP inhibition of nuclear YAP is distinct from other known mechanisms of Hippo regulation. Pharmacologic targeting of specific cAMP microdomains remains an untapped therapeutic approach for cancer; thus, drugs directed at the nuclear cAMP microdomain may provide avenues for the treatment of cancer.

Spatially mapping the immune landscape of melanoma using imaging mass cytometry.

Melanoma is an immunogenic cancer with a high response rate to immune checkpoint inhibitors (ICIs). It harbors a high mutation burden compared with other cancers and, as a result, has abundant tumor-infiltrating lymphocytes (TILs) within its microenvironment. However, understanding the complex interplay between the stroma, tumor cells, and distinct TIL subsets remains a substantial challenge in immune oncology. To properly study this interplay, quantifying spatial relationships of multiple cell types within the tumor microenvironment is crucial. To address this, we used cytometry time-of-flight (CyTOF) imaging mass cytometry (IMC) to simultaneously quantify the expression of 35 protein markers, characterizing the microenvironment of 5 benign nevi and 67 melanomas. We profiled more than 220,000 individual cells to identify melanoma, lymphocyte subsets, macrophage/monocyte, and stromal cell populations, allowing for in-depth spatial quantification of the melanoma microenvironment. We found that within pretreatment melanomas, the abundance of proliferating antigen-experienced cytotoxic T cells (CD8+CD45RO+Ki67+) and the proximity of antigen-experienced cytotoxic T cells to melanoma cells were associated with positive response to ICIs. Our study highlights the potential of multiplexed single-cell technology to quantify spatial cell-cell interactions within the tumor microenvironment to understand immune therapy responses.

Multi-omic analysis reveals significantly mutated genes and DDX3X as a sex-specific tumor suppressor in cutaneous melanoma.

The high background tumor mutation burden in cutaneous melanoma limits the ability to identify significantly mutated genes (SMGs) that drive this cancer. To address this, we performed a mutation significance study of over 1,000 melanoma exomes, combined with a multi-omic analysis of 470 cases from The Cancer Genome Atlas. We discovered several SMGs with co-occurring loss-of-heterozygosity and loss-of-function mutations, including PBRM1, PLXNC1 and PRKAR1A, which encodes a protein kinase A holoenzyme subunit. Deconvolution of bulk tumor transcriptomes into cancer, immune and stromal components revealed a melanoma-intrinsic oxidative phosphorylation signature associated with protein kinase A pathway alterations. We also identified SMGs on the X chromosome, including the RNA helicase DDX3X, whose loss-of-function mutations were exclusively observed in males. Finally, we found that tumor mutation burden and immune infiltration contain complementary information on survival of patients with melanoma. In summary, our multi-omic analysis provides insights into melanoma etiology and supports contribution of specific mutations to the sex bias observed in this cancer.

Publisher Correction: Inference of RNA decay rate from transcriptional profiling highlights the regulatory programs of Alzheimer's disease.

The original version of this Article contained an error in Figure 3, where panel d was inadvertently replaced with a duplicate of panel c during typesetting. Also, the legend of Figure 5f incorrectly read '310 AD patients (blue dots, r = -0.4) and 157 non-demented individuals (green dots, r = -0.1)', and should have read '310 AD patients (blue dots, r = -0.1) and 157 non-demented individuals (green dots, r = -0.4)'. Both of these errors have now been corrected in both the PDF and HTML versions of the Article.

Inference of RNA decay rate from transcriptional profiling highlights the regulatory programs of Alzheimer's disease.

The abundance of mRNA is mainly determined by the rates of RNA transcription and decay. Here, we present a method for unbiased estimation of differential mRNA decay rate from RNA-sequencing data by modeling the kinetics of mRNA metabolism. We show that in all primary human tissues tested, and particularly in the central nervous system, many pathways are regulated at the mRNA stability level. We present a parsimonious regulatory model consisting of two RNA-binding proteins and four microRNAs that modulate the mRNA stability landscape of the brain, which suggests a new link between RBFOX proteins and Alzheimer's disease. We show that downregulation of RBFOX1 leads to destabilization of mRNAs encoding for synaptic transmission proteins, which may contribute to the loss of synaptic function in Alzheimer's disease. RBFOX1 downregulation is more likely to occur in older and female individuals, consistent with the association of Alzheimer's disease with age and gender."mRNA abundance is determined by the rates of transcription and decay. Here, the authors propose a method for estimating the rate of differential mRNA decay from RNA-seq data and model mRNA stability in the brain, suggesting a link between mRNA stability and Alzheimer's disease."

Mitochondrial mutations drive prostate cancer aggression.

Nuclear mutations are well known to drive tumor incidence, aggression and response to therapy. By contrast, the frequency and roles of mutations in the maternally inherited mitochondrial genome are poorly understood. Here we sequence the mitochondrial genomes of 384 localized prostate cancer patients, and identify a median of one mitochondrial single-nucleotide variant (mtSNV) per patient. Some of these mtSNVs occur in recurrent mutational hotspots and associate with aggressive disease. Younger patients have fewer mtSNVs than those who diagnosed at an older age. We demonstrate strong links between mitochondrial and nuclear mutational profiles, with co-occurrence between specific mutations. For example, certain control region mtSNVs co-occur with gain of the MYC oncogene, and these mutations are jointly associated with patient survival. These data demonstrate frequent mitochondrial mutation in prostate cancer, and suggest interplay between nuclear and mitochondrial mutational profiles in prostate cancer.In prostate cancer, the role of mutations in the maternally-inherited mitochondrial genome are not well known. Here, the authors demonstrate frequent, age-dependent mitochondrial mutation in prostate cancer. Strong links between mitochondrial and nuclear mutational profiles are associated with clinical aggressivity.

Translating a Prognostic DNA Genomic Classifier into the Clinic: Retrospective Validation in 563 Localized Prostate Tumors.

BACKGROUND: Localized prostate cancer is clinically heterogeneous, despite clinical risk groups that represent relative prostate cancer-specific mortality. We previously developed a 100-locus DNA classifier capable of substratifying patients at risk of biochemical relapse within clinical risk groups. OBJECTIVE: The 100-locus genomic classifier was refined to 31 functional loci and tested with standard clinical variables for the ability to predict biochemical recurrence (BCR) and metastasis. DESIGN, SETTING, AND PARTICIPANTS: Four retrospective cohorts of radical prostatectomy specimens from patients with localized disease were pooled, and an additional 102-patient cohort used to measure the 31-locus genomic classifier with the NanoString platform. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The genomic classifier scores were tested for their ability to predict BCR (n=563) and metastasis (n=154), and compared with clinical risk stratification schemes. RESULTS AND LIMITATIONS: The 31-locus genomic classifier performs similarly to the 100-locus classifier. It identifies patients with elevated BCR rates (hazard ratio=2.73, p<0.001) and patients that eventually develop metastasis (hazard ratio=7.79, p<0.001). Combining the genomic classifier with standard clinical variables outperforms clinical models. Finally, the 31-locus genomic classifier was implemented using a NanoString assay. The study is limited to retrospective cohorts. CONCLUSIONS: The 100-locus and 31-locus genomic classifiers reliably identify a cohort of men with localized disease who have an elevated risk of failure. The NanoString assay will be useful for selecting patients for treatment deescalation or escalation in prospective clinical trials based on clinico-genomic scores from pretreatment biopsies. PATIENT SUMMARY: It is challenging to determine whether tumors confined to the prostate are aggressive, leading to significant undertreatment and overtreatment. We validated a test based on prostate tumor DNA that improves estimations of relapse risk, and that can help guide treatment planning.