An exploration of immunohistochemistry-based prognostic markers in patients undergoing curative resections for colon cancer

Background The immune system recognizes and destroys cancer cells. However, cancer cells develop mechanisms to avoid detection by expressing cell surface proteins. Specific tumour cell surface proteins (e.g. HLA-G, PD-L1, CDX2) either alone or in combination with the relative presence of immune cells (CD3 and CD8 positive T-cells) in the tumour tissue may describe the cancer cells’ ability to escape eradication by the immune system. The aim was to investigate the prognostic value of immunohistochemical markers in patients with colon cancer. Methods We conducted a retrospective study including patients diagnosed with pT3 and pT4 colon cancers. Immunohistochemical staining with HLA-G, PD-L1, CDX2, CD3, and CD8 was performed on tissue samples with representation of the invasive margin. PD-L1 expression in tumour cells and immune cells was reported conjointly. The expression of CD3 and CD8 was reported as a merged score based on the expression of both markers in the invasive margin and the tumour centre. Subsequently, a combined marker score was established based on all of the markers. Each marker added one point to the score when unfavourable immunohistochemical features was present, and the score was categorized as low, intermediate or high depending on the number of unfavourable stains. Hazard ratios for recurrence, disease-free survival and mortality were calculated. Results We included 188 patients undergoing colon cancer resections in 2011–2012. The median follow-up was 41.7 months, during which 41 (21.8%) patients had recurrence and 74 (39.4%) died. In multivariable regression analysis positive HLA-G expression (HR = 3.37, 95%CI [1.64–6.93]) was associated with higher recurrence rates, while a preserved CDX2 expression (HR = 0.23, 95%CI [0.06–0.85]) was associated with a lower risk of recurrence. An intermediate or high combined marker score was associated with increased recurrence rates (HR = 20.53, 95%CI [2.68–157.32] and HR = 7.56, 95%CI [1.06–54.16], respectively). Neither high expression of PD-L1 nor high CD3-CD8 score was significantly associated with recurrence rates. Patients with a high CD3-CD8 score had a significantly longer DFS and OS. Conclusions In tumour cells, expression of HLA-G and loss of CDX2 expression were associated with cancer recurrence. In addition, a combination of certain tumour tissue biomarkers was associated with colorectal cancer recurrence.

Mono-ADP-ribosylation sites of human CD73 inhibit its adenosine-generating enzymatic activity

CD73-derived adenosine plays a major role in damage-induced tissue responses by inhibiting inflammation. Damage-associated stimuli, such as hypoxia and mechanical stress, induce the cellular release of ATP and NAD+ and upregulate the expression of the nucleotide-degrading purinergic ectoenzyme cascade, including adenosine-generating CD73. Extracellular NAD+ also serves as substrate for mono-ADP-ribosylation of cell surface proteins, which in human cells is mediated by ecto-ADP-ribosyltransferase 1 (ARTC1). Here we explored, whether human CD73 enzymatic activity is regulated by mono-ADP-ribosylation, using recombinant human CD73 in the presence of ARTC1 with etheno-labelled NAD+ as substrate. Multi-colour immunoblotting with an anti-etheno-adenosine antibody showed ARTC1-mediated transfer of ADP-ribose together with the etheno label to CD73. HPLC analysis of the enzymatic activity of in vitro-ribosylated CD73 revealed strong inhibition of adenosine generation in comparison to non-ribosylated CD73. Mass spectrometry of in vitro-ribosylated CD73 identified six ribosylation sites. 3D model analysis indicated that three of them (R328, R354, R545) can interfere with CD73 enzymatic activity. Our study identifies human CD73 as target for ARTC1-mediated mono-ADP-ribosylation, which can profoundly modulate its adenosine-generating activity. Thus, in settings with enhanced release of NAD+ as substrate for ARTC1, assessment of CD73 protein expression in human tissues may not be predictive of adenosine formation resulting in anti-inflammatory activity.

Large Scale Discovery of Microbial Fibrillar Adhesins and Identification of Novel Adhesive Domain Families

Fibrillar adhesins are bacterial cell surface proteins that mediate interactions with host cells during colonisation and with other bacteria during biofilm formation. These proteins are characterised by a stalk that projects the adhesive domain closer to the binding target. Fibrillar adhesins evolve quickly and thus can be difficult to computationally identify, yet they represent an important component for understanding bacterial host interactions. To detect novel fibrillar adhesins we developed a random forest prediction approach based on common characteristics we identified for this protein class. We applied this approach to Firmicute and Actinobacterial proteomes, yielding over 4,000 confidently predicted fibrillar adhesins. To verify the approach we investigated predicted fibrillar adhesins that lacked a known adhesive domain. Based on these proteins, we identified 21 sequence clusters representing potential novel adhesive domains. We used AlphaFold to verify that 14 clusters showed structural similarity to known adhesive domains such as the TED domain. Overall our study has made a significant contribution to the number of known fibrillar adhesins and has enabled us to identify novel adhesive domain families involved in the bacterial pathogenesis.

ANTH domains within CALM, HIP1R, and Sla2 recognize ubiquitin internalization signals

Attachment of ubiquitin (Ub) to cell surface proteins serves as a signal for internalization via clathrin-mediated endocytosis (CME). How ubiquitinated membrane proteins engage the internalization apparatus remains unclear. The internalization apparatus contains proteins such as Epsin and Eps15, which bind Ub, potentially acting as adaptors for Ub-based internalization signals. Here we show that additional components of the endocytic machinery including CALM, HIP1R, and Sla2 bind Ub via their N-terminal ANTH domain, a domain belonging to the superfamily of ENTH and VHS domains. Structural studies revealed that Ub binds with µM affinity to a unique C-terminal region within the ANTH domain not found in ENTH domains. Functional studies showed that combined loss of Ub-binding by ANTH-domain proteins and other Ub-binding domains within the yeast internalization apparatus caused defects in the Ub-dependent internalization of the GPCR Ste2 that was engineered to rely exclusively on Ub as an internalization signal. In contrast, these mutations had no effect on the internalization of Ste2 engineered to use an alternate Ub-independent internalization signal. These studies define new components of the internalization machinery that work collectively with Epsin and Eps15 to specify recognition of Ub as an internalization signal.

Transcription Factor Control of Dendrite Targeting via Combinatorial Cell-Surface Codes

Transcription factors are central commanders specifying cell fate, morphology, and physiology while cell-surface proteins execute these commands through interaction with cellular environment. In developing neurons, it is presumed that transcription factors control wiring specificity through regulation of cell-surface protein expression. However, the number and identity of cell-surface protein(s) a transcription factor regulates remain largely unclear1,2. Also unknown is whether a transcription factor regulates the same or different cell-surface proteins in different neuron types to specify their connectivity. Here we use a lineage-defining transcription factor, Acj6 (ref. 3), to investigate how it controls precise dendrite targeting of Drosophila olfactory projection neurons (PNs). Quantitative cell-surface proteomic profiling of wild-type and acj6 mutant PNs in intact developing brains and a proteome-informed genetic screen identified PN surface proteins that execute Acj6-regulated wiring decisions. These include canonical cell adhesion proteins and proteins previously not associated with wiring, such as the mechanosensitive ion channel Piezo—whose channel activity is dispensable for its wiring function. Comprehensive genetic analyses revealed that Acj6 employs unique sets of cell-surface proteins in different PN types for dendrite targeting. Combinatorial expression of Acj6 wiring executors rescued acj6 mutant phenotypes with higher efficacy and breadth than expression of individual executors. Thus, a key transcription factor controls wiring specificity of different neuron types by specifying distinct combinatorial expression of cell-surface executors.

Detection of subtype-specific Breast Cancer Surface Protein Biomarkers via a novel Transcriptomics approach

Background: Cell-surface proteins have been widely used as diagnostic and prognostic markers in cancer research, and as targets for the development of anti-cancer agents. So far, very few attempts have been made to characterize the surfaceome of breast cancer patients, particularly in relation with the current molecular breast cancer (BRCA) classification. In this view, we developed a new computational method to infer cell-surface protein activities from transcriptomics data, termed “SURFACER”. Methods: Gene expression data from GTEx were used to build a normal breast network model as input to infer differential cell-surface proteins activity in BRCA tissue samples retrieved from TCGA vs. normal samples. Data were stratified according to the PAM50 transcriptional subtypes (Luminal A, Luminal B, HER2, Basal), while unsupervised clustering techniques were applied to define BRCA subtypes according to cell-surface proteins activity. Results: Our approach led to the identification of 213 PAM50 subtypes-specific deregulated surface genes and the definition of 5 BRCA subtypes, whose prognostic value was assessed by survival analysis, identifying a cell-surface activity configuration at increased risk. The value of the SURFACER method in BRCA genotyping was tested by evaluating the performance of 11 different machine learning classification algorithms. Conclusions: BRCA patients can be stratified into 5 surface activity-specific groups having the potential to identify subtype-specific actionable targets to design tailored targeted therapies, or for diagnostic purposes. SURFACER-defined subtypes show also a prognostic value, identifying surface-activity profiles at higher risk.