Pan-Cancer TCGA Analysis Reveals the Potential Involvement of Lamin B2 in Dysregulating Chromosome Segregation in Human Cancer

doi:10.21203/rs.3.rs-4697731/v1

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Pan-Cancer TCGA Analysis Reveals the Potential Involvement of Lamin B2 in Dysregulating Chromosome Segregation in Human Cancer

https://doi.org/10.21203/rs.3.rs-4697731/v1

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Lamins are fibrous proteins present just beneath the inner nuclear membrane and play a crucial role in shaping the genomic architecture. Several studies have reported the association of lamins with disease conditions such as cancer. Despite significant progress, the prognostic significance and underlying molecular targets of B-type lamins, especially lamin B2 in pan-cancer, have not been well studied. In this study, we have explored through bioinformatic analysis the potential functions of lamin B2 in driving cancer and its prognostic significance across pan-cancer TCGA datasets. Our results indicate the overexpression of lamin B2 in multiple human cancers, which is also correlated with poor overall and disease-free survival. Besides this, higher lamin B2 is associated with CD4⁺ Th1 and Th2 cell infiltration. We have identified 9 lamin B2 interacting proteins that are co-expressed with lamin B2 in cancerous conditions and, together with lamin B1, regulate cytokinesis and cell division pathways. Furthermore, we have identified specific molecular targets and independent functions of lamin B2 in dysregulating chromosome segregation and mRNA binding in multiple cancers. Our study, for the first time, has demonstrated the potential functions of lamin B2 and its prognostic significance across different cancers.

Cancer

Lamin B2

TCGA

biomarker

Lamins are fibrous proteins located just beneath the inner nuclear membrane and provide an anchoring platform for genome organization (Dittmer and Misteli 2011; Kim et al. 2019a). Principally, lamins are composed of type V intermediate filaments. There are two types of lamins: A and B; while one single gene LMNA codes A-type lamins (lamin A and lamin C), two B-type lamins (lamin B1 and lamin B2) are coded by two different genes, LMNB1 and LMNB2. All three types of lamins share common structural features, but they differ in post-translational modifications (Zheng et al., 2022). Inside the nucleus, lamins interact with large chromatin blocks and form transcriptionally repressive lamina-associated domains (LADs) (Guelen et al., 2008; Shevelyov and Ulianov, 2019). LADs are enriched in H3K9me3 histone methylation, and the altered contact between LAD and nuclear lamins is crucial for gene regulation in multiple cellular processes, including differentiation and senescence (Guelen et al. 2008; Kind and van Steensel 2010; Peric-Hupkes et al. 2010; Meuleman et al. 2013; van Steensel and Belmont 2017; Briand and Collas 2020).

Abnormal nuclear morphology is long been thought to be a hallmark of cancer (Zink et al. 2004; Singh and Lele 2022). The irregular nuclear shape has been reported in breast cancer, cervical cancer, prostate cancer, and ovarian cancer (Singh and Lele, 2022). Several studies to date have also reported the involvement of lamins in disease conditions, including cancer (Irianto et al. 2016). Despite numerous efforts in this field, the exact role of lamins in tumorigenesis remains uncertain. For instance, lamin B1 expression is elevated in hepatocellular carcinoma (Lim et al. 2002; Sun et al. 2010; Wong and Luk 2012) and prostate cancer (Luo et al. 2021), while the downregulation of the lamin B1 is also reported for multiple cancers such as gastric cancer (Moss et al. 1999; Yu et al. 2020), colon cancer (Moss et al. 1999) and lung cancer (Jia et al. 2019). Recently, Qin et al. (2022) have shown the prognostic significance and potential functions of lamin B1 in pan-cancer based on TCGA data analysis (Qin et al. 2022). Similar to lamin B1, lamin B2 has also been reported in cancers such as the bladder (Ji et al. 2022), colorectal (Dong et al. 2021), and triple-negative breast cancer (Zhao et al. 2021). Nevertheless, there is no systematic study that showcases the involvement of lamin B2 in pan-cancer and its prognostic significance.

In this present study, we have performed a systematic analysis of lamin B2 at the pan-cancer level. Briefly, we have employed the TCGA RNA-seq datasets for all the cancers and analyzed the mRNA expression of lamin B2 across these cancers. Further, we have correlated the expression status of lamin B2 with the clinical outcome to showcase its prognostic significance in all cancers. As tumor-infiltrating immune cells are one the major components of the tumor microenvironment and also one of the major factors that control the drug efficacy in treating cancer, we have correlated the lamin B2 expression with the immune profile across different cancer types. Lastly, we identified, through bioinformatic analysis, unique molecular mechanisms and gene targets that, together with lamin B2, potentially drive the cancer progression in most of the cancers. To the best of our knowledge, this is the first pan-cancer study based on lamin B2, which indicates the potential involvement of lamin B2 in controlling chromosome segregation in cancer.

2.1. Gene expression analysis:

The expression of lamin B2 across pan-cancer TCGA datasets was analyzed through the TIMER2.0 web tool [timer.cistrome.org (Li et al. 2020)]. The gene expression heat map of lamin B1 and lamin B2 was analyzed through the TNMplot server [https://tnmplot.com (Bartha and Győrffy 2021)]. We have employed the UALCAN webserver [https://ualcan.path.uab.edu (Chandrashekar et al. 2017, 2022)] for the analysis of stage-specific lamin B2 gene expression for multiple cancer types. UALCAN provides a platform for easily exploring, analyzing, and visualizing carcinoma genomic, transcriptomics, and proteomics profile data, allowing users to combine these data for improved comprehension and reveal the genes, protein molecules, and pathways disrupted in cancer. The UALCAN web portal allows members of the cancer scientific community to analyze and distribute cancer transcriptome, proteome, and patient survival data (Chandrashekar et al. 2017, 2022). We investigated lamin B2 expression in ovarian cancer stage-wise using TCGA data through the UALCAN webserver.

2.2. Gene correlation analysis:

The top 100 correlated genes for lamin B2 across all TCGA cancers were extracted from the GEPIA2 tool [http://gepia2.cancer-pku.cn (Tang et al. 2019)]. GEPIA (Gene Expression Profiling Interactive Analysis) is an online program based on TCGA and GTEx data that provides rapid and customized functionality. Analysis of differential expression, profiling graphing, correlation analysis, survival of patients, comparable gene recognition, and reduction of dimensionality analysis are just a few of the interactive and customizable features available in GEPIA (Tang et al. 2017; Li et al. 2021). Further, for the generation of a correlation matrix of lamin B2 and individual signature genes, we have employed the TIMER2.0 web tool.

2.3. Survival analysis:

Overall survival (OS) has been defined as the time of cancer diagnosis till the time of death, while disease-free survival (DFS) has been defined as the time after treatment during which no sign of cancer has been noted. We have used GEPIA2 for the analysis of overall and disease-free survival with a high lamin B2 expressing cohort and a low lamin B2 expressing cohort. Survival heat maps based on hazard ratios were also calculated using GEPIA2.

2.4. Immune infiltration analysis:

Tumor Immune Estimation Resource (TIMER) was developed as an open-access tool that will assist cancer biologists in analyzing and illustrating the huge number of tumor-infiltrating immune cells (TIICs) extensively and flexibly [timer.cistrome.org (Li et al. 2020)]. To determine the abundance of TIICs through gene expression profiles, TIMER employs a deconvolution approach. It can help determine the type of cancer as well as particular TIIC subsets that correlate with the expression of a particular gene of interest, given that cancerous cells and TIICs communicate through many genetic products as well as pathways during tumor growth and progression (Li et al. 2020). TIMER was used to investigate the association between lamin B2 expression in ovarian cancer patients and the abundance of six immune infiltrates, comprising macrophages, neutrophils, B cells, CD4⁺ T cells, CD8⁺ T cells, and dendritic cells. The scatter plots exhibit partial Spearman's rho corrected for purity.

2.5. Functional enrichment analysis:

TNM Plot facilitates real-time comparisons of gene expression variations between tumor, normal, and metastatic tissues across all genes on several platforms. It is a comprehensive repository that utilizes transcriptome-level data [https://tnmplot.com (Bartha and Győrffy 2021)]. TNMplot has been utilized to calculate the gene expression profile in normal and tumor tissues in the case of ovarian cancer. Moreover, for the functional enrichment analysis of the selected signature genes, we have utilized the 'functional enrichment' module of the TNMplot tool to calculate the GO (gene ontology) biological process and molecular functions.

2.6. Cell lines and cell culture:

Human epithelial ovarian cancer cell lines A2780, IGROV1, OVCAR3, OVCAR4, OVACAR5, and OVCAR8 were grown on RPMI1640 media supplemented with 10% fetal bovine serum (FBS) and 1% antibiotic-antimycotic solution at 37^oC in presence of 5% CO₂. Human Immortalized ovarian surface epithelium (IOSE364) cell line was grown on a 1:1 mixture of MCDB105 and Medium199 supplemented with 5% FBS and 1% antibiotic-antimycotic solution at 37^oC in the presence of 5% CO₂.

2.7. Western blot analysis:

IOSE and EOC cell lines were grown at 70% confluence and harvested and lysed in radioimmunoprecipitation lysis buffer (RIPA) supplemented with protease inhibitors. The lysate was sonicated thrice with 35% amplitude with 10 secs on/off cycle. Extracted proteins were estimated using the Bradford method. 30 µg of total proteins from each sample were separated on 10% sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and electro-transferred onto charged polyvinylidene difluoride membranes (Millipore, Billerica, MA) at 90 volts for 90 min at 4°C. Membranes containing transferred proteins were blocked with 5% BSA [prepared in 1X Tris-buffered saline (TBST)] at room temperature for 1 hour. After blocking, the membranes were incubated with primary antibodies prepared in blocking solution overnight at 4°C. Primary antibodies used include mouse anti-Lamin B2 (ab8983; 1:1000 dilution) and rabbit anti-Beta-actin (ab8227; 1:1000 dilution). Membranes were washed after primary antibody incubation with 1X TBST for 3 times (5 min each) and incubated with HRP-conjugated secondary antibodies at 37°C for 1 hour. Secondary antibodies used include anti-rabbit-HRP [ab6721 (1: 2000 dilution); Cat# 7074P2 (Cell Signalling Technologies)] and anti-mouse HRP [Cat# 7076P2 (Cell Signalling Technologies; 1:2000 dilution]. Blots were washed with 1X TBST for 3 times after secondary antibody incubation. Chemiluminescent signals were detected using Image Quant LAS500 (GE) gel doc system. The intensity of the bands was determined by densitometric analysis using Image J software.

2.8. Statistical Analysis:

Statistical significance for lamin B2 expression in normal vs tumor tissue were calculated through Mann-Whitney test. The cell line screening data (densitometric quantification of lamin B2 expression from western blot analysis) represent mean ± standard deviation (SD) and statistical significance were calculated through one-way ANOVA. Statistical siignificace for Kaplan-Meier survival analysis were calculated through log-rank test. P < 0.05 were considered as statistically significant for all the analysis.

3.1. Lamin B2 is upregulated in multiple cancers:

We first checked the expression of lamin B2 in pan-TCGA cancers using the TIMER2.0 web tool. We found that out of 33 cancers, 21 cancers show higher expression of lamin B2 in cancer conditions than in normal (non-cancerous) tissues. The cancers which show significant high expression of lamin B2 include bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), oesophageal carcinoma (ESCA), head and neck squamous cell carcinoma (HNSC), kidney renal cell carcinoma (KIRC), kidney chromophobe (KIRP), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), prostate adenocarcinoma (PRAD), rectum adenocarcinoma (READ), stomach adenocarcinoma (STAD), thyroid carcinoma (THCA) and uterine corpus endometrial carcinoma (UCEC) [Fig. 1a]. As lamin B1 expression is also upregulated in multiple cancers and correlated with poor prognosis, we have analyzed the expression of both lamin B1 and lamin B2 in pan-cancer using TNMplot [Fig. 1b]. We found that Lamin B2 expression is even higher than lamin B1 in a subset of cancers, making it more interesting to explore its prognostic significance further. Further, we have explored how the expression of lamin B2 is correlated with clinical stages in the cancers that showed significant overexpression from Fig. 1a. Using the UALCAN web server, we have found that the expression of lamin B2 is almost constant across clinical stages except for breast invasive carcinoma where the expression is low in stage 1 but increases with stage 2 and remains almost constant till stage 4 [Fig. S1 (Online Resource 1)]. We further experimentally validated that lamin B2 protein expression is elevated in high-grade serous ovarian cancer cell lines (Except OVACR5) as compared to the non-cancerous cell line IOSE364 [Fig. 1c-d].

3.2. Prognostic significance of lamin B2 overexpression in cancer:

To elucidate the prognostic significance of lamin B2 in human cancers, we employed the GEPIA2 tool. The overall and disease-free survival was analyzed for lamin B2 in pan-TCGA cancer datasets as well as individual cancer datasets. We found that both the overall and disease-free survival decreases with high lamin B2 expression in the pan-cancer module with P value < 0.0001, suggesting a clear prognostic significance of lamin B2 overexpression in all the cancers (Fig. 2a). Next, we investigated the cancer-specific prognostic significance of lamin B2. We have used the 'survival map' module of the GEPIA2 web tool to calculate the significant hazard ratio associated with lamin B2 overexpression in individual cancer. Our results identified 8 cancer types for which high expression of lamin B1 is associated with poor overall survival, while we found only one cancer where lamin B2 overexpression leads to better overall survival. The cancer types which showed poor prognosis with lamin B2 overexpression include ACC (P < 0.0001), LGG (P < 0.0001), LIHC (P = 0.012), LUAD (P = 0.0013), MESO (P < 0.0001), PRAD (P = 0.0041), SARC (P = 0.0069) and SKCM (P = 0.015); while THYM showed better prognostic outcome (P = 0.022) [Fig. 2b].

3.3. Lamin B2 expression is associated with immune infiltration in cancer:

Increasing pieces of evidence suggest that the tumor microenvironment is an important factor that controls tumor aggression and failure of conventional chemotherapy (Neophytou et al. 2021; Wang et al. 2023). Therefore, understanding tumor microenvironment and tumor-immune cell interaction is a key factor for a complete understanding of tumor biology. This led us to ask how the overexpression of lamin B2 in different tumors affects the tumor-infiltrating immune cells. To address our question, we have used TIMER2.0 to calculate the correlation between lamin B2 and different tumor-infiltrating immune cells in pan-cancer based on TCGA data. We found lamin B2 overexpression in almost all the cancers, leading to an increase in the infiltration levels of CD4⁺ Th1 and Th2 Cells [Fig. 3a]. The cancers for which the association between lamin B2 expression and CD4⁺ T cell infiltration levels are highly significant include ACC (spearman r = 0.679), BLCA (spearman r = 0.623), BRCA (spearman r = 0.517), ESCA (spearman r = 0.559), MESO (spearman r = 0.549), CHOL (spearman r = 0.549), READ (spearman r = 0.511) and THYM (Spearman r = 0.727) [Fig. 3b].

3.4. Lamin B2, along with lamin B1, is associated with the regulation of cytokinesis for cancer development:

To further elucidate the functions of lamin B2 in promoting carcinogenesis, we have extracted the top 100 lamin B2 correlated genes across all TCGA cancers using the GEPIA2 webserver. The top 10 genes which had similar expression patterns with lamin B2 in all the cancers include MKI67, CHAF1A, NCAPH, PLK1, DAZAP1, CDCA5, KIF2C, KIF4A and TPX2. Table S1 (online resource 2) shows list of top 100 lamin B2 correlated genes in pan-cancer analysed by utilizing TCGA data through GEPIA2 tool. To identify how many of the lamin B2 correlated genes are the interacting partners of lamin B2, we have listed the top 100 binding partners of lamin B2 from the STRING database for which the association is experimentally determined (with low confidence). The top 10 binding partners of lamin B2 (as per confidence score) which were experimentally validated include MAPK1 (Mitogen-activated protein kinase 1; score = 0.75), MAPK3 (Mitogen-activated protein kinase 3; score = 0.75), LMNA (lamin-A/C; score = 0.741), LEMD3 (Inner nuclear membrane protein Man1; score = 0.633), LMNB1 (lamin B1; score = 0.63), TTC7A (Tetratricopeptide repeat protein 7A; score = 0.533), BANF1 (Barrier-to-autointegration factor; score = 0.526), LRRK2 (Leucine-rich repeat serine/threonine-protein kinase 2; score = 0.494), EXOSC9 (Exosome complex component RRP45; score = 0.402) and IQSEC1 (IQ motif and SEC7 domain-containing protein 1; score = 0.394). We present the list of top 100 lamin B2 interacting proteins identified from STRING (with experimental validation) in Table S2 (Online Resource 2). Out of the 100 lamin B2 correlated genes, we found 9 of them are the lamin B2 binding proteins, suggesting that these proteins are co-expressed in different cancers with lamin B2 and modulate potential pathways that promote tumor growth and progression [Fig. 4a]. These 9 genes include MCM2, MCM4, KIF23, KIF14, KIF20A, MKI67, ZNF598, PRC1 and lamin B1. We computed the Spearman correlation of each of these genes with lamin B2 in pan-TCGA cancer datasets using GEPIA2 and found all 9 genes have significant correlation with lamin B2 in pan-TCGA cancer datasets having the correlation coefficient of 0.81 (MKI67), 0.8 (MCM2), 0.78 (KIF14, KIF23, MCM4, PRC1), 0.77 (LMNB1), 0.75 (KIF20A) and 0.71 (ZNF598) [Fig. 4b]. To determine the cancer types where these genes show maximum correlated expression with lamin B2, we have computed a correlation heatmap of lamin B2 with these 9 signature genes across individual cancer types using the TIMER2.0 tool [Fig. 4c]. We found a positive correlation between these signature genes and lamin B2 in almost all cancer types except for UCS, where only KIF20A and MKI67 genes are positively correlated with lamin B2 with a significant p-value [Fig. 4c]. Out of those cancer types that show a positive correlation with lamin B2, we have noted that 8 cancer types show a very strong positive correlation of lamin B2 with almost all 9 signature genes [Fig. 5b]. These cancers include ACC, GBM, LGG, LIHC, LUAD, MESO, STAD and THYM. Interestingly, except for THYM, almost all these cancers show poor prognosis with lamin B2 overexpression. This also suggests that lamin B2 mediated molecular alterations are disseminated through these 9 signature proteins in those cancers. Expression analysis of these 9 signature genes across different cancers also confirms that these genes are upregulated in tumors compared to normal tissues [Fig. 4e]. To further identify the biological processes that are affected by these genes, we performed the GO enrichment analysis using the TNMplot web tool. The biological processes that are mostly affected by these proteins include the regulation of cytokinesis, cell division, and mitotic division [Fig. 4d]. We have further checked the effect of these 9 signature genes on the overall and disease-free survival. We found 8 cancers where overexpression of most of the genes leads to a significant decrease in overall survival. Amongst them, ACC, LGG, and LIHC are the ones where both overall and disease-free survival is affected by overexpression of all the 9 signature genes [Fig. 5a & c]. Notably, THYM showed better survival outcomes by overexpression of these signature genes.

3.5. Lamin B2 independently regulates chromosome segregation and mRNA binding for tumor pathogenesis:

We have noted that lamin B1 is one of the correlated genes of lamin B2. Lamin B1 overexpression is well-reported in a range of human cancers. A pan-cancer study based on TCGA data analysis also showcases its prognostic significance and underlying molecular targets in cancer (Qin et al., 2022). To identify lamin B2-specific functions in cancer, we have computed the number of genes that exclusively interact with lamin B2 and not lamin B1 and co-express with lamin B2 in different cancers. From GEPIA2, we have computed the top 100 lamin B1 correlated genes in all TCGA cancer, and from the STRING tool, we have identified the top 100 lamin B1 interacting proteins. The list of top 100 lamin B1 correlated genes identified from TCGA datasets in pan-cancer and top 100 lamin B1 interacting proteins were listed in Table S3 and Table S4 (Online Resource 2) respectively. Then, we compared lamin B2 interacting and correlated genes with lamin B1 interacting and correlated genes. We found that 59 of the lamin B2 correlated genes are also correlated with lamin B1 across pan-cancer tissues. Within the remaining 41 lamin B2 correlated genes, 1 gene serves as a common interacting partner of lamin B2 and lamin B1. We have identified 2 genes as specific lamin B2 interacting and correlated genes expressed in multiple cancers [Fig. 6b]. One of them is lamin B1 itself, as lamin B1 interacts with lamin B2 and is co-expressed with lamin B2 in human cancer. Another exclusive partner is ZNF598 (Zinc finger protein 598), which is correlated with lamin B2 [Fig. 6b]. For further analysis, we have only considered ZNF598 as we intended to identify the molecular targets and functional significance exclusive to lamin B2. We prepared a protein-protein interaction network through the STRING web tool, which includes exclusive interacting partners of lamin B2 and ZNF598, the common element between exclusive lamin B2 correlated and interacting partners. We found that 27 of the lamin B2 interacting proteins are forming a protein network that is connected via ZNF598 to lamin B2 [Fig. 6a]. To further look into the functional aspect of this network, we have performed a functional enrichment analysis of these proteins, which form a protein network with lamin B2 along with ZNF598. Among the enriched terms, we found 'chromosome segregation,' 'sister chromatin segregation,' 'nuclear chromosome segregation,' 'mitotic nuclear division' as the top gene ontology (GO) biological processes and 'mRNA 3’-UTR binding' as the top GO molecular functions [Fig. 6d]. To further elucidate our findings in the context of cancer, we asked how the genes involved in 'chromosome segregation' and 'mRNA 3’-UTR binding' pathways are correlated with lamin B2 in different cancers to showcase that lamin B2 mediates alteration in these processes in cancer, as mentioned above. We identified 10 signature genes specifically associated with lamin B2, which are involved in 'chromosome segregation' and 'mRNA 3’-UTR binding'. We found that lamin B2 is significantly correlated with these 10 signatures in almost all cancer types, which indicates that upregulation of lamin B2 in several cancers leads to changes in chromosome segregation and mRNA binding [Fig. 6c]. We extended this observation to find out the clinical outcome of the co-expression of lamin B2 and these 10 signature genes, performed an overall survival analysis and calculated the hazard ratio. We identified 5 cancer types, namely ACC, LGG, LIHC, LUAD, and SKCM, for which the overexpression of almost all the 10 signature genes individually leads to poor prognosis and decreased overall survival [Fig. 7a]. The Spearman correlation analysis between lamin B2 and the combined 10 signature genes in these 5 cancer types and the combined pan-TCGA RNA seq datasets show a strong positive correlation with significant p-value [Fig. 7b]. The Spearman correlation coefficient values of lamin B2 and 10 signature genes are 0.86 (combined TCGA RNA-seq datasets; termed as Pan-TCGA cancer), 0.87 (ACC), 0.77 (LGG), 0.79 (LIHC), 0.81 (LUAD) and 0.73 (SKCM) [Fig. 7b]. Even the expression analysis of these 10 signature genes through TNMplot for LUAD and LIHC has shown that the expression of these genes is elevated in metastatic tumors [Fig. 7c]. Lastly, we have performed an overall survival analysis using GEPIA2 with high and low expression cohort of combined 10 signature genes in the previously identified 5 cancer types and found that the elevated expression of combined 10 signature genes in all 5 types of cancers as well as in the pan-cancer module leads to poor overall survival of patients [Fig. 7d]. These results, in turn, suggest that lamin B2-mediated alteration of chromosome segregation may be a key process in tumorigenesis for several human cancers.

Lamins are one of the principal components of the nuclear lamina and control genome organization, gene transcription, and nuclear plasticity (Martin et al. 2009; Kim et al. 2019b; Wong et al. 2021; Nazer 2022). Lamins develop molecular contact with a large portion of the genome by forming lamina-associated domains (LADs) that are transcriptionally repressed (Guelen et al., 2008). The interaction between lamins and the genome is highly dynamic, and many genes tend to shift their position and reorganize themselves inside the nucleus in a number of conditions, including cellular differentiation, lineage commitment, senescence, and diseases to become transcriptionally active (Peric-Hupkes et al. 2010; Kind and Van Steensel 2014; Luperchio et al. 2014; Lochs et al. 2019; Kundu et al. 2021). Increased mutational burden and transcriptional dysregulation of lamins are reported for multiple disease conditions collectively termed 'laminopathies' as well as in cancer (Worman and Bonne 2007; Irianto et al. 2016). Previous studies have demonstrated that the functions of different lamins in contributing to cancer development and progression are different in different cancers.

Nevertheless, lamin B2, one of the two B-type lamins, is comparatively less studied in the context of tumorigenesis. Even some studies show ambiguous results for lamin B2 in controlling tumor growth. Here, we have done a pan-cancer level study to understand how lamin B2 plays an important role in tumorigenesis and which cancers are primarily affected by lamin B2 overexpression and its related pathway through in-silico analysis of RNA-seq and microarray datasets. Our in-silico study based on TCGA data analysis revealed the significant overexpression of lamin B2 in 21 different types of cancers. Also, it showcased that in some cancers, the level of expression is even higher than lamin B1, which suggests that lamin B2 has important functions in controlling neoplastic transformation. Consistent with the previously published reports of lamin B2 upregulation in bladder (Ji et al. 2022), lung (Zhang et al. 2020), colorectal (Dong et al. 2021), triple-negative breast cancer (Zhao et al. 2021) and hepatocellular carcinoma (Kong et al. 2020), our study also reported the overexpression of lamin B2 in other cancers such as CESC, CHOL, ESCA, HNSC, KICH, KIRC, KIRP, LUSC, READ, SKCM, STAD and UCEC for which no study regarding lamin B2 expression and cancer progression was done previously. We further elucidated that overexpression of lamin B2 leads to poor prognosis at the pan-cancer level, both in the context of overall survival and disease-free survival.

Insights from previous studies indicated the role of lamins in controlling cellular proliferation, invasion, and metastasis in multiple cancers. Dong et al. (2021) reported that lamin B2 promotes tumorigenesis in colorectal cancer by regulating p21 (Dong et al. 2021). In another study, Ji et al. (2022) reported that lamin B2 transcriptionally activates cell division cycle-associated protein 3 (CDCA3) in bladder cancer and thereby controls the proliferation of bladder cancer cells (Ji et al. 2022). In order to gain a clear understanding of the functionality of lamin B2 in driving cancer, we have identified which of the lamin B2 binding partners are co-expressed with lamin B2 in all cancers. Our in-silico study based on publicly available TCGA datasets has identified the association between lamin B2 and mini-chromosome maintenance protein MCM2 and MCM4 as well as several members of kinesin family members such as KIF14, KIF20A, and KIF23. The kinesin family member 20A (KIF20A) has been well reported to be overexpressed in multiple cancers, and higher expression is correlated with poor prognosis (Jin et al., 2023).

Interestingly, KIF20A is also reported as an important driving factor for chemotherapy resistance in colorectal cancer (Xiong et al. 2019). Recent research from Jiang et al. (2023) also reported the involvement of KIF14 in driving the proliferation, metastasis, and chemoresistance in cholangiocarcinoma (Jiang et al. 2023). In a different study, Cheng et al. (2020) showed that both KIF14 and KIF23 promote chemoresistance in hepatocellular carcinoma (Cheng et al. 2020). These results suggest a strong link between lamin B2 overexpression and the development of chemoresistance in multiple cancers, and they also open up a new avenue of research in this field. The correlation between lamin B2 and MKI67 in multiple cancers is also self-explanatory in stating the involvement of lamin B2 in controlling cell proliferation in cancer. Interestingly, our data showcase lamin B1 as one of the common genes between lamin B2 interacting partners and lamin B2 correlated genes. As functions of lamin B1 are well noted in the case of multiple human cancers as well as in pan-cancer from TCGA data analysis (Hua et al. 2022; Yang et al. 2022; Saleh et al. 2022; Qin et al. 2022), we focused more on the lamin B2 specific functions that play a key role during tumorigenesis.

We identified 10 signature genes that are specific to lamin B2 and not lamin B1 and co-expressed with lamin B2 in most cancers. Gene ontology enrichment showcases that these genes are involved in chromosome segregation and mRNA 3'UTR binding. Several of these signature genes individually are associated with poor overall patient survival in at least 5 different cancers, including ACC, LGG, LIHC, LUAD, and SKCM. An increased expression of all 10 genes together also showed decreased overall patient survival. ZNF598 has been previously reported as an E3 ubiquitin ligase protein and is involved in mRNA binding and directing polyadenylated premature ribosome proteins towards ubiquitinylation (Garzia et al. 2017). Although the role of lamin B2 in cancer is not well defined in the literature, our in-silico results indicate a significant positive correlation between lamin B2 expression and ZNF598 expression. This finding suggests new directions to explore in the study of lamin B2-mediated ubiquitinylation of premature ribosomal proteins.

Nevertheless, the other members of the 10 signature genes are involved in several cancer-related pathways. The X-ray repair cross-complementing group 3 (XRCC3) gene is a DNA homologous recombination and crosslink repair-related gene that, when overexpressed, increases the risk associated with breast and thyroid cancer (Liu et al. 2021). Another member within the 10-signature group, FEN1 (flap endonuclease 1), is also a DNA repair gene, and overexpression of this gene is associated with several cancers, including breast, pancreatic, prostate, lung, and gastric cancer (Balian and Hernandez 2021). Although originally discovered as a tumor suppressor gene, recent studies have also established its role in cancer development and progression (Wei et al. 2021). Our finding that lamin B2 is positively correlated with these genes in several cancers strongly suggests that lamin B2-mediated modulation of the DNA repair pathway is also one of the important factors in driving neoplastic transformation.

On the other hand, the positive correlation between lamin B2 and the cell cycle regulator protein CDC20, cell division cycle associated 8 (CDCA8), and spindle and kinetochore associated complex subunit 1 (SKA1) in multiple cancer types indicates its potential role also in cell cycle regulation, chromosome segregation, and cell division. CDC20 plays a major role in proper chromosome segregation and promoting mitosis (Kapanidou et al. 2017) and has been recently reported as a novel biomarker for epithelial ovarian cancer (Xi et al. 2022). Recently, Ji et al. (2022) reported that lamin B2 mediates the proliferation of bladder cancer cells through activation of cell division cycle associated 3 (CDCA3), which is highly consistent with our data (Ji et al. 2022). On the other hand, CDCA8, an important member of the chromosomal passenger complex (CPC complex), is involved in proper chromosome segregation and has also been reported to overexpress in malignant tumors. Downregulation of CDCA8 in prostate cancer cell lines has been shown to reduce the migration and invasion of prostate cancer cells (Wan et al., 2022). Another component, SKA1, a member of the kinetochore-associated protein complex, is also a protein involved in proper chromosome segregation (Hanisch et al. 2006; Schmidt et al. 2012). Pan-cancer analysis based on publicly available datasets has previously shown that SKA1 is overexpressed in multiple cancers and associated with poor prognosis (Lan et al., 2023).

Moreover, in vitro studies have shown that downregulation of SKA1 through shRNA in adenosquamous carcinoma cell lines resulted in cell cycle arrest and apoptosis (Zhang et al. 2013). This study further strengthens our observation that lamin B2-driven tumor pathogenesis is mediated by dysregulation of chromosome segregation and mitotic divisions that promote abrupt cell proliferation and survival of cancer cells. Thus, taken together, our study showcases lamin B2 as a potential biomarker for most cancers along with lamin B1 and indicates a previously underexplored pathway for lamin B2-mediated tumor pathogenesis.

Declaration of Interest:

The authors report no financial and non-financial conflict of interest.

Funding:

The work was supported by grants from the Science and Engineering Research Board, Department of Science and Technology (DST-SERB), Govt. of India with grant no. ECR/2016/001740 and Indian Council of Medical Research (grant no. 5/3/8/31/ITR-F/2022-ITR). SK, thanks to the University Grants Commission, India, for fellowship support.

Author Contribution

S.K. was involved in conceptualization, visualization, methodology, data analysis, data interpretation and manuscript writing; B.P.J. was involved in manuscript writing, reviewing and editing; A.S. was involved in manuscript writing, reviewing, editing, supervision and funding acquisition. All authors read and reviewed the final manuscript.

Acknowledgement

The authors thank All India Institute of Medical Sciences, New Delhi, India, for providing all necessary support. The authors thank all members of the Laboratory of Chromatin and Cancer Epigenetics, Department of Biochemistry, AIIMS, New Delhi, for all the valuable discussions and support.

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Pan-Cancer TCGA Analysis Reveals the Potential Involvement of Lamin B2 in Dysregulating Chromosome Segregation in Human Cancer

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Abstract

Figures

1. Introduction

2. Materials and Methods

2.1. Gene expression analysis:

2.2. Gene correlation analysis:

2.3. Survival analysis:

2.4. Immune infiltration analysis:

2.5. Functional enrichment analysis:

2.6. Cell lines and cell culture:

2.7. Western blot analysis:

2.8. Statistical Analysis:

3. Results

3.1. Lamin B2 is upregulated in multiple cancers:

3.2. Prognostic significance of lamin B2 overexpression in cancer:

3.3. Lamin B2 expression is associated with immune infiltration in cancer:

3.5. Lamin B2 independently regulates chromosome segregation and mRNA binding for tumor pathogenesis:

4. Discussion

Declarations

Declaration of Interest:

Funding:

Author Contribution

Acknowledgement

References

Additional Declarations

Supplementary Files

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