The optimal interval before receiving SARS-COV-2 vaccination for patients who have received Anti-CD 20 monoclonal antibodies

The optimal interval before receiving SARS-COV-2 vaccination for patients who have received anti-CD 20 monoclonal antibodies remains unclear. We considered original studies up to 29 October 2022 and conducted searches in Embase,Medrxiv, PubMed, and SSRN. We excluded search results that did not match our research question’s subject. Human immune response outcomes were analysed inpatients who had previously received anti-CD20 antibody therapy. We analyzed the collected results using sensitivity curves and forest plots. Twenty-eight studies with a total of 1455 subjects receiving anti-CD20 monoclonal antibodies were included in the present analysis. The humoral immune response rates to the time between the last anti-CD20 treatment and vaccination for 3–6 months, 6 months,6–9 months, and 9–12 months were 0.23 (95% CI 0.14 to 0.36), 0.36 (95% CI 0.19 to 0.58), 0.49 (95% CI 0.35 to 0.64) and 0.64 (95% CI 0.48 to 0.77),respectively. The humoral immune response rates were.16 (95% CI 0.03 to 0.57) when B cell was 0/ul, and 0.49 (95% CI 0.38 to 0.61)when B cells were more than 5/ul. The humoral immune response rate for multiple sclerosis was 0.39 (95% CI 0.22 to 0.60) and 0.48 (95% CI 0.29 to 0.68) for B-cell non-Hodgkin lymphoma. The area underneath the curve(AUC) was 0.69 with a cut-off value of 5.5 months. The present results suggested that the optimal interval for SARS-COV-2 vaccination after the final dose of anti-CD20 monoclonal antibody was 5.5 months.</p

System-Wide Analysis Reveals a Complex Network of Tumor-Fibroblast Interactions Involved in Tumorigenicity

<div><p>Many fibroblast-secreted proteins promote tumorigenicity, and several factors secreted by cancer cells have in turn been proposed to induce these proteins. It is not clear whether there are single dominant pathways underlying these interactions or whether they involve multiple pathways acting in parallel. Here, we identified 42 fibroblast-secreted factors induced by breast cancer cells using comparative genomic analysis. To determine what fraction was active in promoting tumorigenicity, we chose five representative fibroblast-secreted factors for <i>in vivo</i> analysis. We found that the majority (three out of five) played equally major roles in promoting tumorigenicity, and intriguingly, each one had distinct effects on the tumor microenvironment. Specifically, fibroblast-secreted amphiregulin promoted breast cancer cell survival, whereas the chemokine <i>CCL7</i> stimulated tumor cell proliferation while <i>CCL2</i> promoted innate immune cell infiltration and angiogenesis. The other two factors tested had minor (<i>CCL8</i>) or minimally (<i>STC1</i>) significant effects on the ability of fibroblasts to promote tumor growth. The importance of parallel interactions between fibroblasts and cancer cells was tested by simultaneously targeting fibroblast-secreted amphiregulin and the <i>CCL7</i> receptor on cancer cells, and this was significantly more efficacious than blocking either pathway alone. We further explored the concept of parallel interactions by testing the extent to which induction of critical fibroblast-secreted proteins could be achieved by single, previously identified, factors produced by breast cancer cells. We found that although single factors could induce a subset of genes, even combinations of factors failed to induce the full repertoire of functionally important fibroblast-secreted proteins. Together, these results delineate a complex network of tumor-fibroblast interactions that act in parallel to promote tumorigenicity and suggest that effective anti-stromal therapeutic strategies will need to be multi-targeted.</p></div

Comparative genomic analysis of expression changes induced by breast cancer cells in tumor-supportive fibroblasts, patient-derived carcinoma-associated fibroblasts, and microdissected breast stroma.

<p>(A) Top ten pathways identified by GSEA analysis of exposure of tumor-supportive fibroblasts to breast cancer cells; blue indicates overlap with the top ten pathways activated in patient-derived breast cancer fibroblasts; green indicates overlap with other pathways significantly activated in patient-derived breast cancer fibroblasts; grey indicates no overlap, (B) Top ten pathways identified by GSEA analysis of patient-derived breast cancer fibroblasts relative to their normal counterparts; blue indicates overlap with the top ten pathways activated by exposure of tumor-supportive fibroblasts to breast cancer cells; green indicates overlap with other pathways significantly activated by exposure of tumor-supportive fibroblasts to breast cancer cells; grey indicates no overlap, (C) Top ten pathways identified by GSEA analysis of microdissected breast cancer stroma relative to normal breast stroma, green indicates overlap with pathways significantly activated by exposure of tumor-supportive fibroblasts to breast cancer cells, but not in the top ten; grey indicates no overlap. (D) A tumor-supportive fibroblast gene signature was used in unsupervised clustering to classify normal (green) and tumor (red) microdissected breast stroma samples. (E) The same signature was used in principal component analysis to observe the separation of normal (green) and tumor (red) microdissected breast stroma samples.</p

Amphiregulin is a chemoattractant for fibroblasts and helps prevent necrosis and tumor cell death.

<p>(A) Photomicrographs of mouse fibroblasts that have transversed a Boyden chamber in response to different concentrations of amphiregulin in the opposing chamber. Migration was measured 5 hours post plating. Scale bars represent 100 µm. (B) Amphiregulin promotes migration of mouse embryonic fibroblasts (MEFs) in a scratch wound-healing assay (photomicrographs at indicated time after initiation of assay). (C) Quantification of the Boyden migration assay. Data are expressed as the mean ± SEM. Asterisks indicate a significant difference (p<0.05) between experimental and control groups. (D) Quantification of migration in scratch wound healing assay (cells that had moved into the scratched area as percent of control). Asterisk indicates a significant difference between the control and experimental group (p<0.05). (E) Quantitative RT-PCR analysis of α-SMA expression (relative to GAPDH) in HFFF2 fibroblasts (gray bars) and Wi38 fibroblasts (red bars) upon treatment with amphiregulin. Asterisk indicates a significant difference between untreated HFFF2 fibroblasts and those treated at 50 and 100 ng/ml (p value 0.01 and 0.001, respectively). All data are expressed as the mean ± SEM. (F) Necrosis in Cal51+HFFF2 tumors with control shRNA or with shRNA targeting <i>AREG</i> as visualized by H&E staining. Dashed lines indicate necrotic areas. Scale bars represent 1 mm. (G) Quantification of necrosis in Cal51+HFFF2 tumors with control shRNA or with shRNA targeting <i>AREG</i>. Necrotic area was calculated from five different tumors per group. Data are expressed as the mean ± SEM. Asterisks indicate a significant difference (p = 3e-4) between experimental and control groups. (H) EGFR activation (phosphorylation) in Cal51+HFFF2 tumors with control shRNA or with shRNA targeting <i>AREG</i> detected by immunostaining using an antibody to phospho-EGFR (Tyr1068). Scale bars represent 50 µm. (I) Quantification of phospho-EGFR positive tumor cells in Cal51+HFFF2 tumors with control shRNA or with shRNA targeting <i>AREG</i>. Areas positive for pEGFR were calculated from five different fields of five different tumors per group. Asterisk indicates that the experimental group is significantly different than the control (p = 0.007). Data are expressed as the mean ± SEM. (J) Effects of amphiregulin on the viability of Cal51 cells plated on non-adhesive plates and cultured for 24 hours (anoikis assay). Viability was determined by measuring calcein AM uptake. Asterisk indicates that the experimental group is significantly different than the control (p<0.05). Data are expressed as the percentage of viable cells normalized to control with the error bars representing SEM.</p

42 secreted proteins selectively induced by breast cancer cells in tumor-promoting fibroblasts.

<p>Results of literature searches on the 42 secreted proteins selectively induced in tumor-supportive fibroblasts. Descriptions are from Ingenuity (<a href="http://www.ingenuity.com" target="_blank">www.ingenuity.com</a>). Semi-automated searches were performed using the gene symbols and different search terms (e.g. stromal fibroblast, tumor microenvironment, cancer) with PubMatrix (pubmatrix.grc.nia.nih.gov).</p

Combined inhibition of chemokine and amphiregulin signaling is more effective at blocking the effects of tumor supportive fibroblasts.

<p>(A) Paracrine upregulation of the expression of ligand-receptor pairs upon co-culture of tumor supportive fibroblasts with basal breast cancer cells. The fold-change in ligand expression in tumor-supportive fibroblasts (x-axis) is plotted along with the fold-change in receptor expression in breast cancer cells (y-axis). (B) Tumorigenicity of Cal51 cells expressing either control shRNA or shRNAs targeting <i>CCR1</i> co-injected with HFFF2 fibroblasts. Tumor take rate for each group is indicated. Asterisks indicate significant differences in tumor volumes for shCCR1-1 and shCCR1-2 co-injection groups compared to control (p<0.01) (C) Tumorigenicity of Cal51 and HFFF2 fibroblasts coinjected in the following combinations: Cal51 cells expressing shRNAs targeting <i>CCR1</i> co-injected with HFFF2 fibroblasts expressing control shRNA; Cal51 cells expressing control shRNA coinjected with HFFF2 cells expressing shRNA targeting AREG; Cal51 cells expressing shRNAs targeting <i>CCR1</i> co-injected with HFFF2 fibroblasts expressing shRNA targeting AREG. Tumor take rate for each group is indicated. Asterisks indicate significant differences (p<0.05). (D) Histological and Immunohistochemical analysis of the effects of suppressing CCR1 in Cal51 cells and amphiregulin in tumor-supportive fibroblasts HFFF2 as described in the legend to <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003789#pgen-1003789-g002" target="_blank">Figure 2</a> but also tumor necrosis which was evaluated on hematoxylin and eosin stained sections. Scale bars represent 50 µm for Ki67 and 7/4, 100 µm for α-SMA and 500 µm for hematoxylin and eosin staining. (E) Quantification of microenvironment effects as described in the legend to <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003789#pgen-1003789-g002" target="_blank">Figure 2</a>. Five different fields of three different tumors per group were scored. Error bars represent SEM. Hashtag indicates a significant difference in proliferation in the CCR1 silenced group compared to the control where p = 8.9E-04. Asterisk indicates a significant difference in proliferation in the CCR1 and AREG silenced group compared to the control where p = 0.01. (F) Similarly performed quantification of neutrophils and monocytes where Hashtag indicates a significant difference in the CCR1 silenced group compared to the control where p = 4.6E-04. Asterisk indicates a significant difference in the CCR1 and AREG silenced group compared to the control where p = 2.4E-05. (G) Similarly performed quantification of activated mesenchymal cells. Asterisk indicates a significant difference in the CCR1 and AREG silenced group compared to the control where p = 0.003. (H) Similarly performed quantification of necrotic area. Asterisk indicates a significant difference in the CCR1 and AREG silenced group compared to the control where p = 0.02.</p

Tumor-supportive fibroblasts have profound effects on the composition of the tumor microenvironment.

<p>(A) Tumor-supportive fibroblasts HFFF2 increase Cal51 tumor cell proliferation and increase stromal components (bottom panel) as compared to tumors formed using Cal51 alone (top panel). Immunohistochemical analysis using antibodies to Ki-67 (proliferation), antigen #7/4 (neutrophils and monocytes), CD31 (blood vessels), and α-SMA (mesenchymal cells). Scale bars represent 50 µm for Ki-67, #7/4 and CD31 and 100 µm for α-SMA. (B) Quantification of Ki-67 positive (proliferating) tumor cells. Five different fields of three different tumors per group were scored. Asterisk indicates a significant difference between cell line only (Cal51shNT) and co-injection (Cal51shNT+HFFF2) groups (p<0.01). Data are expressed as the mean ± SEM. (C–E) Similarly performed quantification of monocytes and neutrophils, endothelial cells, and activated mesenchymal cells (p<0.01).</p

Additional file 2 of Characterization of Auxenochlorella protothecoides acyltransferases and potential of their protein interactions to promote the enrichment of oleic acid

Additional file 2: Table S1. QPCR primers used for quantitative analysis of the expression level of ApDGATs in A. protothecoides UTEX 2341. Table S2. Primers used for cloning of the full-length coding sequence of A. protothecoides ApDGATs and ApACBPs. Table S3. Proteins used for amino acid alignment of ApDGATs. Table S4. DGAT proteins used for the construction of the phylogenetic tree. Table S5. Primers used for cloning the truncated coding sequence of ApDGAT1 and ApDGAT2b. Table S6. Overview of putative DGATs and ACBPs cDNAs identified in the A. protothecoides genomic database. Table S8. Fusion expression primers of ApACBPs with ApDGAT1 and ApDGAT2

Data from: Genetic connectivity constrained by natural barriers in a key agricultural pest: Insights from mitochondrial DNA analysis

The original mtDNA data and the R code for random forest model used in the study 'Genetic connectivity constrained by natural barriers in a key agricultural pest: Insights from mitochondrial DNA analysis'.</p

Diverse effects on the tumor microenvironment mediated by fibroblast secretion of the related chemokines CCL2, CCL7 and CCL8.

<p>(A) Immunohistochemical analysis of the effects of suppressing <i>CCL2</i>, <i>CCL7</i> or <i>CCL8</i> in tumor-supportive fibroblasts on cancer cell proliferation, immune cell recruitment, blood vessel recruitment and mesenchymal cell activation in Cal51 tumors, using antibodies to Ki-67 (proliferation), antigen #7/4 (immune cells; neutrophils and monocytes), CD31 (endothelial cells of blood vessels) and α-SMA (mesenchymal cell activation). Scale bars represent 50 µm for Ki-67, antigen #7/4 and CD31 panels and 100 µm for α-SMA. (B–E) Quantification of tumor cell proliferation, monocytes and neutrophils, blood vessel endothelial cells, and mesenchymal cell activation. For each property, five different fields of three different tumors per group were scored. Data are expressed as the mean ± SEM. Asterisks indicates a significant difference between the experimental shRNAs and control non-targeting shRNA (p<0.01). # indicates a significant difference in proliferation in Cal51 only group compared to Cal51 coinjected with HFFF2 fibroblasts (p<0.01). Data are expressed as the mean ± SEM.</p