|
 
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| ORIGINAL ARTICLE |
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| Year : 2019 | Volume
: 11
| Issue : 1 | Page : 37-48 |
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Candidate Genes for Suicide Risk in Head and Neck Squamous Cell Carcinoma Patients
Anusa Arunachalam Mohandoss1, Rooban Thavarajah2, Elizabeth Joshua3, Umadevi Krishnamohan Rao3, Kannan Ranganathan3
1 Department of Psychiatry, Shri Satya Sai Medical College and Research Institute, Affiliated to Shri Balaji Vidyapeeth, Ammapettai, Kanchipuram, India
2 Marundeeshwara Oral Pathology Services and Analytics, Shollinganallur; Department of Oral and Maxillofacial Pathology, Ragas Dental College and Hospital, Affiliated to the Tamil Nadu Dr. MGR Medical University, Uthandi, Chennai, India
3 Department of Oral and Maxillofacial Pathology, Ragas Dental College and Hospital, Affiliated to the Tamil Nadu Dr. MGR Medical University, Uthandi, Chennai, India
| Date of Web Publication | 9-Aug-2019 |
Correspondence Address:
Prof. Rooban Thavarajah
Consultant and Director, Marundeeshwara Oral Pathology Services and Analytics B-1, Mistral Apartments, Wipro Street, Shollinganallur, Chennai - 600 119
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/jofs.jofs_2_19
Intoduction: Suicide is relatively more common among cancer patients as compared to general population. There are several identified candidate genes for suicide (CGS). There is a dearth of research examining the association of differential expression (DE) of CGS among the treatment-naïve head and neck squamous cell carcinoma (HNSCC) patients. The present study was undertaken to identify the DE of messenger Ribo Nucleic Acid (mRNA) of CGS in HNSCC tumor and correlate with clinical and other known genetic factors that promote oncogenesis as well as suicide. Material and Methods: Using previously described method, CGS lists were identified. The DE of the mRNA of the CGS were obtained from The Cancer Genome Atlas–HNSCC patients along with clinical details. The DE of mRNA pertaining to known factors such as inflammation, serotonergic, and dopaminergic functions as well as clinical parameters were studied for association with the risk of DE of CGS. Appropriate statistics were performed and P ≤ 0.05 was taken as significant. Results: A total of 520 HNSCC patients formed the study group. There were 46 (8.85%) patients who had DE of CGS. Expression of genes associated with inflammatory signaling pathway, ribosomal protein pathway, mechanistic Target of Rapamycin (mTOR), and metastasis, and invasion set of genes as well as the noradrenergic group of genes were associated significantly with DE of CGS. The association of DE of CGS and the major HNSCC clinical predictors of smoking, human papilloma virus status, clinical and cancer staging, histology grading, as well as patient status were not statistically significant. With a male predilection, gender exhibited statistically significant difference (P = 0.012). Discussion: In cancer patients, transcriptomes have been postulated to mediate suicide by targeted action on human brain. DE of putative genes associated with suicide have been demonstrated in HNSCC tumor. These DEs could predispose the patients to suicidal ideation/behavior in confluence with immediate psychosocial constructs. Addressing depression and suicidal thoughts in cancer patients would help to mitigate the risk of suicide.
Keywords: Candidate genes for suicide, mrna, oral squamous cell carcinoma, suicide, transcriptome
How to cite this article:
Mohandoss AA, Thavarajah R, Joshua E, Rao UK, Ranganathan K. Candidate Genes for Suicide Risk in Head and Neck Squamous Cell Carcinoma Patients. J Orofac Sci 2019;11:37-48 |
How to cite this URL:
Mohandoss AA, Thavarajah R, Joshua E, Rao UK, Ranganathan K. Candidate Genes for Suicide Risk in Head and Neck Squamous Cell Carcinoma Patients. J Orofac Sci [serial online] 2019 [cited 2023 Jun 9];11:37-48. Available from: https://www.jofs.in/text.asp?2019/11/1/37/264184 |
| Introduction | |  |
Head and neck squamous cell carcinoma (HNSCC) is one of the most common cancer globally.[1],[2] In developed countries such as USA, with increased awareness, diagnostic facilities, effective treatment options, and monitoring, the survival rates in HNSCC have improved.[3] The death rates in HNSCC patients from comorbid conditions is also increasing, one of which is suicide.[4] Suicide rates among the HNSCC are reported to be thrice the suicide population. Head and neck ranks among the top five sites associated with suicides in cancer patients. It contributes to upto 20% of cancer-related suicides in USA, although HNSCC only contributes to 3% of the cancer burden.[5],[6],[7],[8],[9]
Suicide ideation, behavior, attempt, and completion often occurs when an individual maladapts in face of negative life events including a diagnosis of cancer. Such individuals are often known to have un (under) diagnosed psychiatric illness and/or addiction or misperceive circumstances and/or overreact in an impulsive manner.[10] Personality trait and the in-depth biology of suicidal brain has been studied in detail in the past.[10],[11],[12],[13],[14],[15],[16] The relationship of suicides with cancer has been recently reported.[17],[18]
Depression, the common presenting mental illness associated with suicide and suicidal ideation (SI), has been previously reported among patients diagnosed with HNSCC ranging from 8% to 20%.[19],[20],[21] A recent study among head and neck cancer patients reported (n = 223 patients) that 0.4% committed suicide within 3 months and 0.9% attempted suicide during the study period. In this cohort, 11.2% had suicidal thoughts and 4% had attempted suicide, prior to cancer diagnosis.[19]
The current concept of suicide is that it is a result of interaction of multicausal risk factors acting distally and proximally to the suicide. Factors such as history of suicides in family, genetic variations, and early-life adversity are some of the distal factors. These factors are related to risk of suicide but have a distant temporal relationship to the crisis that precipitates suicide. The proximal factors are those that precipitate the suicidal crisis directly, such as recent life-altering events, and are often associated with onset of the suicidal psychopathology. It is reported that about 90% of suicide completers meet the criteria laid down for psychiatric disorders in the last 6 months of their life. In such a state, the individual’s problem-solving capacity and judgment are impaired. Such altered depressive states are also often accompanied by molecular changes in the brain.[15],[16] [Figure 1] describes the probable interplay of the proximal and distal factors of suicides related to HNSCC in detail.[15],[16] Cancer is known to modulate neuroendocrine factors,[22] influences hypothalamus-pituitary-adrenal (HPA) gland axis, and promotes depression via inflammation pathways that can precipitate distal factors of suicidal ideation and behavior.[13],[14],[15],[16],[17],[18] | Figure 1 Proximal and distal factors in suicidality in people living with head and neck squamous cell carcinoma
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HNSCC has a variety of mutation of genes along with other genetic alterations (GAs).[23],[24] These GAs alter expression of their associated downstream/upstream differential expressions (DEs), which can be measured in the peripheral blood. Peripheral blood messenger Ribo Nucleic Acid (mRNA)-based markers for HNSCC are also being increasingly reported.[23],[24] There is a new interest in psychiatric research circles to identify peripheral biomarkers of suicidal behavior (SB) and attempt.[10],[27] These studies were able to identify “candidate genes for suicide” (CGS) or suicidal vulnerability due to genes with high accuracy.[10],[27]
At present, the available scientific evidence does not claim the “cause–effect” relationship between CGS and suicidality in cancer patients. The existence of such an association has been confirmed through the longitudinal study of depression, anxiety, suicidality, and alterations in molecular biology of brain in cancer patients.[17],[19],[20],[21] There are not too many studies to associate the CGS DE/GA with HNSCC patients. We attempt to study the altered tumor tissue mRNA expression of CGS in a large set of reported cases of HNSCC patients in a bid to estimate the possible association of the interplay of known set of genes in promoting suicidality or increasing its vulnerability. We hypothesize that (1) a subset of HNSCC patients have alteration in mRNA expression of CGS; (2) factors such as inflammation, HPA axis suppression, ribosomal protein alteration, and serotonergic and noradrenergic gene influence the expression of CGS; and (3) GAs could be distal-proximal factor for suicidality in HNSCC patients and increase the vulnerability.
| Materials and Methods | | |
The data for this study was derived from the cBioCancer Genomics Portal (http://cbioportal.org) using HUGO gene symbols.[28],[29] It is an open-access resource for interactive exploration of multidimensional cancer genomics data sets, currently providing access to data from more than 60,000 tumor samples from 225 cancer studies. The clinical details and the mRNA expression z-score data from HNSCC reported from The Cancer Genome Atlas More Details (TCGA) were included for this study.[30] For any particular gene considered, the mRNA z-scores obtained by processing the Ribonucleic Acid Sequence - RSEM (RNA-Seq by Expectation Maximization), version 2(RNA Seq V2 RSEM) (a software package for estimating gene and isoform expression levels from RNA-Seq data) were at a set threshold of ±3 for this study, as against the ±2 in a bid to increase the quality of the findings. The portal employs the complex data processing algorithm to produce the z-score results, as expressed (above/down) of the set threshold for the expression of mRNA.[30] All data were collected in the first week of September 2018. As the z-score of mRNA expression is a measure of the deviation, only its association with possible suicide risk is analyzed by this study. The impact of the DE would depend on the position of the gene in the various functional pathways, environmental interaction, mutation of the upstream/downstream genes, etc. Hence, this present study would limit only to association of one or more genes expressing altered mRNA in HNSCC with the estimated CGS risk.
The Cancer Genome Atlas (TCGA) definition of patients, clinical details of gender, cancer staging, clinical staging, histology grading, human papilloma virus (HPV) status, patient vital status and disease status (at the last presentation), smoking categories, mutation count, age at diagnosis, aneuploidy score, and disease free (in months) were employed in this study.
Predictor variables in the study
The CGS associated with suicide (behavior, ideation, feeling, or completed) were identified from the following sources: PheGenI (https://www.ncbi.nlm.nih.gov/gap/phegeni) and DisGenet (http://www.disgenet.org). Gene–disease association (score >0) was accessed for suicidal phenotypes and the resultant genes were tabulated under their respective headings.[31],[32] Recent pertinent literature reviews/meta-analysis were manually searched for CGS (in normal and psychiatric patients) and those missing in the above list were classified as “Literature Search.”[33],[34],[35],[36] This search included phenotypic expression such as risk of suicide, SB, SI, suicidal attempt (SA), and those having depression with suicidal risk from their respective web portal. The study population were dichotomized in each of these group (present or absent), when they have DE of mRNA in at least one of the genes involved. The biomarker genes (DE) of CGS, in the study by Niculescu et al. in 2015, was obtained and graded to conclude as high-risk subject or non-high-risk subject, when at least one of the genes were differentially expressed.[27]
The expression (DE/non-DE) of mRNA from TCGA–HNSCC for HPA gland axis, noradrenergic, and serotonergic (concerned with serotonin synthesis, transportation, and receptors) were also collected.[15],[16],[33],[34],[35],[36],[37],[38] The common genes involved with the regulation of ribosomal protein synthesis and cell growth, PI3k–AKT–mTOR signaling pathway, and those with invasion/metastasis as reported in cBioCancer Genomics Portal was collated and their mRNA expression was dichotomized as DE or non-DE as from the website (http://cbioportal.org).[28],[29] DE of genes from the inflammation mediated by chemokine and cytokine signaling pathway were collated as DE or non-DE.[39],[40] The clinical details as described above were also considered as a predictor variable.
Outcome variable
Recent literature cites peripheral biomarkers of suicide by the Indiana University group. The reported biomarkers in 2015 was validated only in psychiatric patients whereas their 2017 report also included nonpsychiatric patients.[10],[27] The 2017 list of biomarkers (listed as BioM 148 Panel, in their manuscript) were collected.[10] The genes that expressed increased mRNA (n = 30) involving three or more genes were categorized as high risk and those with one or two genes were categorized as such, whereas the patients with no altered mRNA expression were marked as “no risk.” Similarly, the genes that were decreased in quantities below normal gene mRNA (n = 96) had all of them being considered (n = 10 genes, in 17 instances) as suicide-risk category. In total, patients were classified as high risk, with one or two genes being expressed and no-risk patients depending on the mRNA expression z-scores with a threshold z-score of ±3. Similarly, the expression of mRNA of genes SLC4AA and CLN5 were also studied.
The data thus collected were entered and analyzed using the Statistical Package for Social Services (SPSS, Version 23, IBM, IL, USA). The predictor variables were compared with the outcome variable using chi-square test, appropriate statistics of one-way analysis of variance, and Kruskal–Wallis test as required.
Postanalysis refinement approach
The mRNA that were DE in at least 2.5% of entire study populations from genes of the “PheGenI,” “DisGenet,” and “Literature Search” lists (please note that 32.1% or 167 patients had no CGS–DE of mRNAs) were subjected to enrichment prioritization studies using Enrichr (http://amp.pharm.mssm.edu/Enrichr) that associates the pathways with significance.[41],[42] The P value from Fisher’s exact test/hypergeometric test, Q value obtained from Benjamini–Hochberg method, and rank scores (z) were obtained. Adjusted P value ≤0.05 was taken as significant.
| Results | | |
From the “PheGenI” (n = 40), “DisGenet” (n = 24), and “Literature Search” (n = 6) genes were listed out and the mRNA expression was analyzed in the HNSCC population. After removing overlaps in the first two and removing the CGS mRNA that were not identified in this cohort, 61 gene products that were expressed in 0.4% to 14.81% of the study population were identified. The individual details are given in [Table 1]. In the CGS panel as suggested by Niculescu et al. (2015), 12.12% of the study population were identified to be high-risk candidates for suicide that was further refined to 8.85% when the biomarker (n = 148) from the Niculescu et al. (2017) list was employed.[10],[27] | Table 1 Frequency of differentially expression (DE) of candidate genes for suicide (CGS) in the study population (n = 520)
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On comparing the risk of suicide, as measured by Niculescu et al. (2017), with their previous biomarkers, the difference was statistically significant with high correlation identified in high-risk suicide group.[10] Inflammatory signaling pathway, ribosomal protein pathway, mTOR, metastasis, and invasion set of genes as well as the noradrenergic group of genes were significantly associated with high risk for suicide [Table 2]. The SLC4A4 mRNA was upregulated in four HNSCC patients (0.77%), CLN5 in a single HNSCC patient (0.19%), and combined in five HNSCC patient (0.96%). Of these five cases, two cases emerged in high-risk list whereas the remaining three cases had one or two genes expressed group. This difference was statistically significant (P = 0.019). | Table 2 Comparison of risk of suicide between various pathways, sets of genes, and databases considered
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The association of DE of CGS and the major HNSCC clinical predictors of smoking, HPV status, clinical and cancer staging, histology grading, as well as patient status were not statistically significant. With a male predilection, gender exhibited statistically significant difference (P = 0.012). Kruskal–Wallis test revealed that the total mutation count and disease-free months were not statistically significant with the risk of suicide whereas one-way analysis of variance revealed no significant difference between age and aneuploidy score. The “PheGenI” and “DisGenet” set of mRNA-expressing genes that were classified as those with risk of suicide, SB, SI, SA, and exhibiting features of depression and suicide. The patients were classified as those with DE and non-DE. On comparing the same with the Niculescu et al.’s (2017)[10] proven biomarker list, statistically significant association emerges with the risk of suicide (P = 0.000), SI (P = 0.005), and SA (P = 0.000) [Table 3],[Table 4],[Table 5]. | Table 3 Clinical parameter’s association with risk of suicide in the study group
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 | Table 4 Clinical parameter’s association with risk of suicide in the study group
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 | Table 5 Comparison of risk of suicide with suicidal predisposition, suicidal ideation, behavior, attempt, and depression
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CGS-DE enrichment prioritization studies using Enrichr indicates that 19 genes fit into this group. These were the STK3, IMPAD1, HTR2C, PLCB1, FKBP5, GRIP1, KIAA1549L, BRINP3, RPS6KC1, TBX20, ACP1, BDNF, XPR1, GDA, PRKCE, REN, CRH, NOS1, and SERPINA6 genes. The P value from Fisher’s exact test/hypergeometric test, Q value obtained from Benjamini–Hochberg method, and rank scores (z) were obtained.
The genes (BDNF, HTR2C, and BRINP3) were attributed to dendrites in the gene ontology cellular component (P = 0.015) and were associated with a lot of mental illness such as major depressive disorder (P = 8.19E-05), posttraumatic stress disorder (P = 0.0003), substance abuse (P = 0.0005), alcohol dependence (P = 0.002), generalized anxiety disorder (P = 0.002), obsessive-compulsive disorder (P = 0.005), and brain ischemia (P = 0.005) as in the Jensen disease database (https://jensenlab.org) [Table 6]. | Table 6 Enrich gene expression/enrichment analysis for the most commonly differentially expressed mRNA in “PheGenI,” “DisGenet,” and “Literature Search” set
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The common tissues that were associated with enriched set of CGS were those involved with dopaminergic system (P = 0.001), blood plasma (P = 0.002), and autonomic nervous system (P = 0.005) as identified with Jensen tissues database of expression. The KEGG 2016 pathway enrichment analysis revealed that long-term depression (P = 0.002) and inflammatory mediators regulation of TRP channels (P = 0.003) were the commonly associated pathways. The NCI nature 2016 pathway identified the interleukin-8 pathway association (P = 0.008) whereas the PANTHERDB 2016 pathway revealed 5-hydroxytrptamine receptor-mediated signaling pathway (P = 0.0003) and alpha adrenergic signaling pathway (P = 0.002). The protein–protein interaction database gave statistical significance of 0.038 to NR3C1 expression with GRIP1, ACP1, and FKBP5 [Table 6].
| Discussion | | |
Suicide is a potentially preventable, public health problem that is rising in incidence. It is often a result of a combination of complex factors, occurring in the wake of life-stressor events such as a diagnosis of cancer or an existential crisis. It is a multicausal act, posing difficulty in identifying the strongest predictive factors, understanding complex neurochemical circuitry or internal cognitive states. Emerging gene/genome-based studies have identified with sufficient statistical power that CGS is an important factor for suicidality.[15],[16],[17],[18] The increasing evidence questions the role of GAs in suicidal tendency as a proximal factor and not as pure distal factor as described in the past.[10],[15],[16],[22]
The association of suicides in several cancers has been well documented, especially in epidemiological studies among patients living with cancer (PLWC) in US, UK, Europe, and India.[3],[4],[5],[6],[7],[8],[9] Most of the genome-wide association studies involving suicides were retrospective, addressed psychiatric patients, and only very few have focused on cancers.[10],[11],[12],[13],[14],[15],[16],[17],[18],[19],[20],[21] Our study attempted to identify the association of DE of mRNA of putative genes that are associated with suicide in a group of HNSCC patients. The present study also correlated with known set of genes influencing cancer as well as those associated with suicides.
The knowledge of circulating transcriptome, especially that of mRNA, has given deep insights in the pathogenesis, diagnosis, and marking prognosis of human cancers, including HNSCC.[25],[26],[44],[45],[46] Like most of the tumors, HNSCC also expresses variety of DE mRNAs, including that of the CGS, which are responsible for abnormal protein, and also, a significant part of them are then released in blood.[45],[46] Studies have established that mRNA remains largely stable even when the blood is coagulated or after 24 hours.[47] By virtue of their capabilities, the mRNA/altered proteins may possibly cross the blood–brain barrier to reach the brain at areas like prefrontal cortex, frontostriatal networks, frontolimbic structures, and hippocampus where they exert their influence via the receptors on the neurons, predisposing them to subjective attribution or attributional errors or existential crisis or depression or interfering with serotoninergic, dopaminergic, adrenalin–noradrenalin, HPA axis, and GABA set of genes, thus creating SI, SB, SA, and completion of suicides or increasing its vulnerability[37],[48],[49],[50],[51] [Figure 2]. | Figure 2 Mechanism of candidate gene for suicide’s mRNA differential expression from the head and neck squamous cell carcinoma influencing brain and leading to suicide. Image modified from: Figure 1 of Solomon et al.[57]
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The present study estimates a CGS–DE risk of suicide or its vulnerability in 8.85% of the HNSCC population studied. The absence of statistically significant correlation between the different categories of smoking, HPV status, clinical and cancer staging, histology grading, patient status, total mutation count, disease-free months, age at diagnosis, aneuploidy score, and the risk of suicide categories (of Niculescu et al., 2017) indicate that these factors does not influence the CGS expression alone. The high statistical correlation of risk of suicide among CGS, SI, and SA indicates that the risk is well grounded. It also helps to establish the existence of other psychosocial–environmental distal factors. Abnormal expression of mRNA of certain CGS increases the risk, strengthening it as a proximal factor rather than as a distal factor alone.[11] The difference also could suggest that suicide may be due to the effect, at least in partial, to incremental changes in DE rather than a complete on–off mechanism, as suggested earlier[27] [Table 3],[Table 4],[Table 5].
The statistically significant difference of risk of suicide or vulnerability among genders has been previously reported in a large-scale US cancer population-based study whereas several other studies contradict the same.[52],[53] The high numbers of males in the HNSCC and possibly the inherent difference between perception and reaction for stress among genders could have contributed to this phenomenon[52] [Table 3].
Serotonergic and HPA axis genes have been implicated in suicides.[14],[15],[16] As most of the PLWC also suffer from varying degrees of clinical depression, the DE of such CGS is often overlooked, as they occur commonly in suicides and PLWC.[19],[20],[21] Hence, the significance of these CGS cannot be overlooked although they do not possess the statistically significant association in this study. The difference in DE of risk of suicide, SI, SB, and SA have to be approached carefully because of overlaps in DE of genes as well their roles in pathways involved. Literature has earlier postulated this difference[27] [Table 2].
The significant association of inflammation mediated by chemokine and cytokine signaling pathway, ribosomal protein synthesis and cell growth set of genes, PI3k–AKT–mTOR signaling pathway, and those with invasion/metastasis-associated genes as well as the noradrenergic group of genes have been previously described in literature.[10],[11],[12],[13],[14],[15],[16],[17],[18] The present study also is in concurrence with the definitive influence of these pathways on suicidal tendency among cancer patients.
When a set of commonly DE–CGS were analyzed using enrichment prioritization studies, it was identified that dendrites were the most commonly involved organelle whereas the dopaminergic system, blood plasma, and autonomic nervous system were commonly associated tissues. The analysis in several different platforms identified that the same set of CGS are commonly associated with many psychiatric illness, especially long-term depression in which suicidal thoughts, SI, SB, SA, and completion are hallmark features. Previous reports of suicidality in cancer indicates the prominent role played by the inflammation, cytokines, interleukins, 5-hydroxy tryptoamine receptor-mediated signaling pathway, and alpha adrenergic signaling pathway.[10],[11],[12],[13],[14],[15],[16],[17],[18] The present approach also confirms the same by the statistical significance in the enrichment analysis. In the present study, the protein–protein interaction database-based analysis identified a statistical significance (P = 0.038) with CGS − NR3C1 with GRIP1, ACP1, and FKBP5. It should be noted that these genes have been associated with suicidality[10],[11],[12],[13],[14],[15],[16],[17],[18] [Table 5] and [Table 6].
From these discussions, it could safely be assumed that there is (1) a definite subset of HNSCC patients who have alteration in mRNA expression of CGS, underlying vulnerability for suicide; (2) the known factors such as inflammation mediated by chemokine and cytokine signaling pathway, ribosomal protein synthesis and cell growth set of genes, PI3k–AKT–mTOR signaling pathway, and those with invasion/metastasis-associated genes as well as the noradrenergic group of genes influence the DE of CGS in the suicide risk patients; (3) there is weak evidence to associate the DE of mRNA of CGS to changes in brain [Table 3], but with reasonable statistical power; and (4) the foregone discussion could relate that GAs or DE for CGS could be a distant or a minor proximal factor and not a distal factor in suicidality in HNSCC patients.
Strength of the present study
In PLWC–HNSCC, occurrence of depression and suicidal tendencies possess additional burden to the oncological team. The screening of all HNSCC patients for SI, SB, SA, and risk of suicide is not possible in all situations. The decrease in quality of life in HNSCC–PLWC is enhanced due to depression and suicide. There have been algorithms suggested to diagnose, monitor, and treat the condition.[54] To the best of our knowledge, this is the first study that attempted to correlate DE of CGS to risk and vulnerability of suicide, SI, SB, and SA among a large cohort of HNSCC patients using public cancer genomic database. The study relies on highly validated, cross-access databases, and large-scale data mining capacities of several online websites using the analytical power of MathLab, which opens door to newer vistas in mental health and oncological researches.[28],[29],[30],[31],[32]
Limitations of the present study
The present study relies on pre-existing knowledge about CGS to choose and prioritize them. During the sequencing, high background levels due to cross-hybridization, narrow dynamic range of detection due to higher background, signal saturation, or both are a possibility, although RNA-sequencing is supposed to be the gold standard. Differences in transcriptome assays, in detection of particular (protein coding), noncoding mRNAs, mRNA transcripts, and protein outputs of a gene besides other circulating free genetic materials hamper the deduction of gene expression within and between tissues. Current body of knowledge is that several multiexon genes undergo alternative splicing, increasing the functional diversity of protein species.[54],[55],[56],[57] This is of importance, given the fact that the genetic mechanism overlaps in suicide, depression, SI, SB, and SA.[11],[12],[13] This could affect the presumed diagnostic ability of the CGS. Also, the studies only concentrates on the association and not the “tightness” of the genetic control of the neural process or dynamic interactions between various neural circuitries.
Being a secondary database analysis, it has the strength of large sample size (n = 520) but with less/absence of adequate clinical details including those pertaining to signs, symptoms, and quantification of depression, SI, SB, SA, and suicides. Also, the effect of the numerous drugs that these patients were exposed to remains unknown. The other limitation is that the study associated only with tumor-level mRNA expression and not in blood or brain. Hence, the findings from the studies should be interpreted with caution, till they are replicated in prospective or a well-designed, independent sample cohort, preferably in multicentric and population settings. The phenotypic heterogeneity of both HNSCC and suicide would still remain a challenge.
Clinical implications
The survival rates among PLWC–HNSCC is increasing and the longevity of life comes with burden of depression and risk of suicide. The ease of access to advanced genomic analysis and identification of known and novel CGS would help the oncological team as well as mental health professionals to identify, monitor, prevent, and possibly treat cases with known risk of suicides, SI, SB, and SA, thereby preventing the unnecessary mortality. This study adds to the notion that CGS could be one of the factors that precipitate SI/SB/SA. The role of DE of CGS in HNSCC patients needs more attention and be studied in well designed, long term follow-up. Also, these genes actively modulate the progression of cancer as well as SI, SB, and SA. Prior knowledge of CGS involvement could identify better psychopharmacotherapeutics, vigilance in this unique subset of patients to enhance the quality of life among PLWC.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
| References | | |
| 1. | Marur S, Forastiere AA. Head and neck squamous cell carcinoma: update on epidemiology, diagnosis, and treatment. Mayo Clinic Proc 2016;91:386-96.  |
| 2. | Kalavrezos N, Scully C. Mouth cancer for clinicians part 2: epidemiology. Dent Update 2015;42:354-6, 358-9. |
| 3. | Kam D, Salib A, Gorgy G, Patel TD, Carniol ET, Eloy JA et al. Incidence of suicide in patients with head and neck cancer. JAMA Otolaryngol Head Neck Surg 2015;141:1075-81. |
| 4. | Massa ST, Osazuwa-Peters N, Christopher KM, Arnold LD, Schootman M., Walker RJ et al. Competing causes of death in the head and neck cancer population. Oral Oncol 2017;65:8-15. |
| 5. | Kaceniene A, Krilaviciute A, Kazlauskiene J, Bulotiene G, Smailyte G. Increasing suicide risk among cancer patients in Lithuania from 1993 to 2012: a cancer registry-based study. Eur J Cancer Prev 2017;26:S197-203. |
| 6. | Misona S, Weiss NS, Fann JR, Redman M, Yueh B. Incidence of suicide in persons with cancer. J Clin Oncol 2008;26:4731-8. |
| 7. | Kumar V, Chaudhary N, Soni P, Jha P. Suicide rates in cancer patients in the current era in United States. Am J Psych Res J 2017;12:11-4. |
| 8. | Osazuwa-Peters N, Boakye EA, Walker RJ, Varavares MA. Suicide: a major threat to head and neck cancer survivorship. J Clin Oncol 2016;34:1151. |
| 9. | Osazuwa-Peters N, Arnold LD, Loux TM, Varvares MA, Schootman M. Factors associated with increased risk of suicide among survivors of head and neck cancer: a population-based analysis. Oral Oncol 2018;81:29-34. |
| 10. | Niculescu AB, Le-Niculescu H, Levey DF, Phalen PL, Dainton HL, Roseberry K et al. Precision medicine for suicidality: from universality to subtypes and personalization. Mol Psychiatry 2017;22:1250-73. |
| 11. | Brezo J, Klempan T, Turecki G. The genetics of suicide: a critical review of molecular studies. Psychiatr Clin N Am 2008;31:179-203. |
| 12. | Bondy B, Buettner A, Zill P. Genetics of suicide. Mol Psychiatry 2006;11:336-51. |
| 13. | Ludwig B, Roy B, Wang Q, Birur B, Dwivedi Y. The life span model of suicide and its neurobiological foundation. Front Neurosci 2017;11:74. |
| 14. | Mirkovic B, Laurent C, Podlipski M-A, Frebourg T, Cohen D, Gerardin P. Genetic Association Studies of suicidal behavior: a review of the past 10 years, progress, limitations, and future directions. Front Psychiatry 2016;7:158. |
| 15. | Turecki G. The molecular bases of the suicidal brain. Nat Rev Neurosci 2014;15:802-16. |
| 16. | Turecki G, Ernst C, Jollant F, Labonte B, Mechawar N. The neurodevelopmental origins of suicidal behavior. Trends Neurosci 2012;35:14-23. |
| 17. | Spoletini I, Gianni W, Caltagirone C, Madaio R, Repetto L, Spalletta G. Suicide and cancer: where do we go from here? Crit Rev Oncol Hematol 2011;78:206-19. |
| 18. | Park S, Hong JP, Lee J-K, Park Y-M, Park Y, Jeon J et al. Associations between the neuron‑specific glucocorticoid receptor (NR3C1) Bcl‑1 polymorphisms and suicide in cancer patients within the first year of diagnosis. Behav Brain Funct 2016;12:22. |
| 19. | Henry M, Rosberger Z, Bertrand L, Klassen C, Hier M, Zeitouni A et al. Prevalenceand risk factors of suicidal ideation among patients with head and neck cancer: longitudinal study. Otolaryngol Head Neck Surg 2018;159:843–852. doi: 10.1177/0194599818776873 |
| 20. | Wu YS, Lin PY, Chien CY, Fang FM, Chiu NM, Hung CF et al. Anxiety and depression in patients with head and neck cancer: 6-month follow-up study. Neuropsychiatr Dis Treat 2016;12:1029-36. |
| 21. | Jansen F, Verdonck-de Leeuw IM, Cuijpers P, Leemans CR, Waterboer T, Pawlita M et al. Depressive symptoms in relation to overall survival in people with head and neck cancer: a longitudinal cohort study. Psychooncology 2018. 27: 2245–2256. doi: 10.1002/pon.4816 |
| 22. | Schuller HM. A new twist to neurotransmitter receptors and cancer. J Cancer Metastasis Treat 2017;3:71-7. |
| 23. | Tan H, Bao J, Zhoua X. Genome-wide mutational spectra analysis reveals significant cancer-specific heterogeneity. Sci Rep 2015;5:12566. |
| 24. | Mountzios G, Rampias T, Psyrri A. The mutational spectrum of squamous-cell carcinoma of the head and neck: targetable genetic events and clinical impact. Ann Oncol 2014;25:1889-900. |
| 25. | Kitamura R, Toyoshima T, Tanaka H, Kawano S, Matsubara R, Goto Y et al. Cytokeratin 17 mRNA as a prognostic marker of oral squamous cell carcinoma. Oncol Lett 2017;14:6735-43. |
| 26. | Faria PC, Sena AA, Nascimento R, Carvalho WJ, Loyola AM, Silva SJ et al. Expression of annexin A1 mRNA in peripheral blood from oral squamous cell carcinoma patients. Oral Oncol 2010;46:25-30. |
| 27. | Niculescu AB, Levey DF, Phalen PL, Le-Niculescu H, Dainton HD, Jain N et al. Understanding and predicting suicidality using a combined genomic and clinical risk assessment approach. Mol Psychiatry 2015;20:1266-85. |
| 28. | Gao J, Aksoy BA, Dogrusoz U, Dresdner G, Gross B, Sumer SO et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal 2013;6:pl1. |
| 29. | Cerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov 2012;2:401–4. |
| 30. | Cancer Genome Atlas Network. Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature 2015;517:576-82. |
| 31. | Ramos EM, Hoffman D, Junkins HA, Maglott D, Phan L, Sherry ST et al. Phenotype-Genotype Integrator (PheGenI): synthesizing genome-wide association study (GWAS) data with existing genomic resources. Eur J Hum Genet 2014;22:144-7. |
| 32. | Piñero J, Bravo À, Queralt-Rosinach N, Gutiérrez-Sacristán A, Deu-Pons J, Centeno E et al. DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants. Nucleic Acids Res 2017;45(D1):D833-9. |
| 33. | Mirkovic B, Laurent C, Podlipski M, Frebourg, Cohen D, Gerardin P. Genetic Association Studies of Suicidal Behavior: a review of the past 10 years, progress, limitations, and future directions. Front Psychiatry 2016;7:158. |
| 34. | Tombácz D, Maróti Z, Kalmár T, Csabai Z, Balázs Z, Takahashi S et al. High-coverage whole-exome sequencing identifies candidate genes for suicide in victims with major depressive disorder. Sci Rep 2017;7:7106. |
| 35. | Zhurov V, Stead JDH, Merali Z, Palkovits M, Faludi G, Schild-Poulter C et al. Molecular pathway reconstruction and analysis of disturbed gene expression in depressed individuals who died by suicide. PLoS One 2012;7:e47581. |
| 36. | Sudol K, Mann JJ. Biomarkers of suicide attempt behavior: towards a biological model of risk. Curr Psychiatry Rep 2017;19:31. |
| 37. | Mormede P, Foury A, Barat P, Corcuff JB, Terenina E, Marissal-Arvy N et al. Molecular genetics of hypothalamic-pituitary-adrenal axis activity and function. Ann N Y Acad Sci 2011;1220:127-36. |
| 38. | Ludwig B, Roy B, Wang Q, Birur B, Dwivedi Y. The life span model of suicide and its neurobiological foundation. Front Neurosci 2017;11:74. |
| 39. | Mi H, Huang X, Muruganujan A, Tang H, Mills C, Kang D, Thomas PD. PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements. Nucleic Acids Res 2017;45(D1):D183-9. |
| 40. | Mi H, Thomas P. Protein networks and pathway analysis. Methods Mol Biol 2009;563:123-40. |
| 41. | Chen EY, Tan CM, Kou Y, Duan Q, Wang Z, Meirelles GV et al. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinform 2013;14:128. |
| 42. | Kulesho-v MV, Jones MR, Rouillard AD, Fernandez NF, Duan Q, Wang Z et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res 2016;44(W1): W90-7. |
| 43. | Mohandoss AA, Thavarajah R. A study on suicide among Indians living with cancer during 2001–2014. Indian J Cancer 2016;53:435-40. [ PUBMED] [Full text] |
| 44. | Fernandez-Mercado M, Manterola L, Larrea E, Goicoechea I, Arestin M, Armesto M et al. The circulating transcriptome as a source of non-invasive cancer biomarkers: concepts and controversies of non-coding and coding RNA in body fluids. J Cell Mol Med 2015;19:2307–23. |
| 45. | Yuan T, Huang X, Woodcock M, Du M, Dittmar R, Wang Y et al. Plasma extracellular RNA profiles in healthy and cancer patients. Sci Rep 2016;6:19413. |
| 46. | Li Y, Elashoff D, Oh M, Sinha U, St John MA, Zhou X et al. Serum circulating human mRNA profiling and its utility for oral cancer detection. J Clin Oncol 2006;24:1754-60. |
| 47. | Tsui NB, Ng EK, Lo YM. Stability of endogenous and added RNA in blood specimens, serum, and plasma. Clin Chem 2002;48:1647-53. |
| 48. | Balcioglu YH, Kose S. Neural substrates of suicide and suicidal behaviour: from a neuroimaging perspective. Psychiatry Clin Psychopharmacol 2018;28:314-28. |
| 49. | Bani-Fatemi A, Tasmim S, Graff-Guerrero A, Gerretsen P, Strauss J, Kolla N et al. Structural and functional alterations of the suicidal brain: an updated review of neuroimaging studies. Psychiatry Res Neuroimaging 2018. doi: 10.1016/j.pscychresns.2018.05.008 |
| 50. | Pandey GN, Rizavi HS, Zhang H, Bhaumik R, Ren X. Abnormal protein and mRNA expression of inflammatory cytokines in the prefrontal cortex of depressed individuals who died by suicide. J Psychiatry Neurosci 2018;43:170-92. |
| 51. | Zhao J, Verwer RWH, Gao SF, Qi XR, Lucassen PJ, Kessels HW et al. Prefrontal alterations in GABAergic and glutamatergic gene expression in relation to depression and suicide. J Psychiatr Res 2018;102:261-74. |
| 52. | Yu GP, Mehta V, Branovan D, Huang Q, Schantz SP. Non-cancer-related deaths from suicide, cardiovascular disease, and pneumonia in patients with oral cavity and oropharyngeal squamous carcinoma. Arch Otolaryngol Head Neck Surg 2012;138:25-32. |
| 53. | Schrijvers DL, Bollen J, Sabbe BG. The gender paradox in suicidal behavior and its impact on the suicidal process. J Affect Disord 2012;138(1-2):19-26. |
| 54. | Henry M, Rosberger Z, Ianovski LE, Hier M, Zeitouni A, Kost K et al. A screening algorithm for early detection of major depressive disorder in head and neck cancer patients post-treatment: Longitudinal study. Psychooncology 2018;27:1622-8. |
| 55. | Yamashita S, Kishino T, Takahashi T, Shimazu T, Charvat H, Kakugawa Y et al. Genetic and epigenetic alterations in normal tissues have differential impacts on cancer risk among tissues. Proc Natl Acad Sci USA 2018;115:1328-33. |
| 56. | Pantazatos SP, Huang YY, Rosoklija GB, Dwork AJ, Arango V, Mann JJ. Whole-transcriptome brain expression and exon-usage profiling in major depression and suicide: evidence for altered glial, endothelial and ATPase activity. Mol Psychiatry 2017;22:760-73. |
| 57. | Solomon I, Voiculescu VM, Caruntu C, Lupu M, Popa A, Ilie MA et al. Neuroendocrine Factors and Head and Neck Squamous Cell Carcinoma: An Affair to Remember. Dis Markers 2018; 9787831. doi: 10.1155/2018/9787831. eCollection 2018 |
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]
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