Genomic Alterations in Oral Multiple Primary Cancers

doi:10.21203/rs.3.rs-3249246/v1

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Genomic Alterations in Oral Multiple Primary Cancers

https://doi.org/10.21203/rs.3.rs-3249246/v1

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Oral squamous cell carcinoma (OSCC) is the predominant type of oral cancer, while some patients may develop oral multiple primary cancers (MPCs) with unclear etiology. This study aimed to investigate the clinicopathological characteristics and genomic alterations of oral MPCs. Clinicopathological data from patients with oral single primary carcinoma (SPC, n=202) and oral MPCs (n=34) were collected and compared. Copy number alteration（CNA）analysis was conducted to identify chromosomal-instability differences among oral MPCs, recurrent OSCC cases, and OSCC patients with lymph node metastasis. Whole-exome sequencing was employed to identify potential unique gene mutations in oral MPCs patients. Additionally, CNA and phylogenetic tree analyses were used to gain preliminary insights into the molecular characteristics of different primary tumors within individual patients. Our findings revealed that, in contrast to oral SPC, females predominated the oral MPCs (70.59%), while smoking and alcohol use were not frequent in MPCs. Moreover, long-term survival outcomes were poorer in oral MPCs. From a CNA perspective, no significant differences were observed between oral MPCs patients and those with recurrence and lymph node metastasis. In addition to commonly mutated genes such as CASP8, TP53 and MUC16, in oral MPCs we also detected relatively rare mutations, such as HS3ST6 and RFP14A. Furthermore, this study also demonstrated that most MPCs patients exhibited similarities in certain genomic regions within individuals, and distinct differences of the similarity degree were observed between synchronous and metachronous oral MPCs.

Biological sciences/Cancer/Head and neck cancer/Oral cancer/Oral cancer detection

Biological sciences/Genetics/Cancer genetics

multiple primary cancers

synchronous

metachronous

copy number alteration

phylogenetic tree.

Oral squamous cell carcinoma (OSCC) is the most prevalent histological subtype of oral cancer, encompassing malignancies that occur in the buccal mucosa, tongue, gingiva, larynx, palate, or lip. The clinical manifestations of OSCC vary depending on the specific cancer type, with some patients presenting with nonhealing nodules or sores in the oral mucosa¹. Others with tumors located in the pharynx or floor of the mouth may experience difficulties in swallowing or changes in vocal quality ². Approximately 75% of OSCC are attributed to alcohol and tobacco use ³. Extensive research has been conducted on OSCC, including studies investigating its clinical presentations, etiology, and treatment strategies.

However, there exist a subset of patients who develop multiple primary cancers (MPCs) in the oral cavity, and the causes of this phenomenon remain unclear. The incidence of MPCs in OSCC ranges from 10–34% and contributes significantly to cancer-related mortality ⁴. As early as 1889, Billroth reported the first case of MPCs, in which a patient developed primary gastric cancer subsequent to epithelial carcinoma of the outer ear, and then in 1932, Warren and Gates proposed diagnostic criteria for MPCs⁵. Currently, the most commonly utilized definitions are provided by the Surveillance Epidemiology and End Results (SEER) project⁶ and the International Association of Cancer Registries and the International Agency for Research on Cancer (IACR/IARC)⁷. The difference in diagnostic criteria between these two systems primarily lies in the statistical analysis of tumor locations. For example, while SEER treats tumors occurring in different parts of the colon as separate entities, the colon is considered a single location in the IACR/IARC system. Additionally, SEER recommends a 2-month interval to differentiate synchronous and metachronous MPCs, whereas the IACR/IARC suggests a cutoff of 6 months to classify tumors as synchronous or metachronous based on the time interval.

With the advancement of modern sequencing technologies, Braakhuis et al. proposed the utilization of molecular diagnostic techniques to accurately identify "True" MPCs in 2002 ⁸. It was postulated that "True" MPCs should exhibit distinct molecular characteristics; however, assessing the degree of similarity between two tumors remains a challenging task. Particularly in cases of malignant tumors with the same histological type occurring in the same organ, distinguishing between primary cancer and metastatic cancer has always posed a dilemma. The IASLC Lung Cancer Staging Project suggests that it is easier to identify differences between the two tumors rather than similarities⁹. The presence of shared characteristics does not definitively indicate that they are the same. Few features can be considered definitive, and many commonly utilized criteria are suggestive but prone to misclassification.

To elucidate the development of oral MPCs, Slaughter et al. introduced the concept of "cancerization of field"¹⁰. These events encompass multi-step and complex processes involving genetic alterations, damage induced by carcinogens such as tobacco and alcohol, human papillomavirus infection¹¹, and other unidentified factors. Researchers have endeavored to identify unique molecular features of secondary oral primary cancers to aid in clinical diagnosis, such as tumor suppressor genes (p53, p14, p73) ¹², FAS/FASLG¹³, p21, p27¹⁴, and oncogenes (MDM2, MDM4) ¹⁵, which may serve as effective molecular markers for MPCs. Furthermore, aberrant methylation levels of CCNA1 and TIMP3 have also been implicated in the development of MPCs¹⁶. However, conclusive evidence supporting these associations is currently lacking. Previously, it was believed that tumors frequently exhibit copy number variation(CNA)events. However, recent reports indicated that the presence of chromosomal aneuploidies in different chromosomes within tumors may potentially serve as a prognostic indicator for distinct tumor outcomes, and could potentially inhibit tumor development¹⁷.

In this study, we established a stringent definition of oral MPCs and conducted a comprehensive clinicopathological analysis. Based on this definition, we employed low-depth CNA sequencing and whole exome sequencing (WES) approaches to explore the molecular distinctions between synchronous and metachronous cancers in different MPCs patients.

Clinicopathological Differences between MPCs and SPCs

A total of 34 MPCs patients were included in our study. The clinical profiles of all 34 patients were summarized in Supplemental Table 1. Among these patients, 4 were synchronous MPCs, while 30 were metachronous MPCs including three patients with tumors in three distinct locations. The mean interval between the initial diagnosis of OSCC and the subsequent tumor in metachronous MPCs was 56 months, ranging from 10 to 144 months.

After a six-year follow-up, we collected data from 202 single primary cancer (SPC) patients to investigate the differences between MPCs and SPC patients. The clinicopathological parameters were analyzed and compared (Table 1). While there was no significant difference in the age at the time of initial diagnosis, a notable gender disparity was observed between the SPC and MPCs groups (p < 0.01). The majority of SPC patients were male (130/202; 64.36%), whereas 70.59% (24/34) of MPCs patients were female. Additionally, we examined the smoking and drinking habits of the two patient groups and found that the proportion of smokers and drinkers was significantly lower in the MPCs group compared to the SPC group (p < 0.01).

Table 1

Comparison of clinicopathological information between MPCs and SPC
		MPCs	SPC	P
Patients		34	202
Gender
	Male	10 (29.41%)	130 (64.36%)	< 0.01
	Female	24 (70.59%)	72 (35.64%)	< 0.01
The mean age at 1st diagnosis(year)		60	58	= 0.418
Smoking
	Yes	6 (17.65%)	122 (60.40%)	< 0.01
	No	28 (82.35%)	80 (39.60%)	< 0.01
Drinking
	Yes	30 (88.24%)	61 (30.20%)	< 0.01
	No	4 (11.76%)	141 (69.80%)	< 0.01
Tumors		71	202
Lymph node metastases
	Yes	12 (16.90%)	78 (38.61%)	< 0.01
	No	59 (83.10%)	124 (61.39%)	< 0.01
Pathology grade
	Well	66 (92.96%)	123 (60.89%)	< 0.01
	Poor	5 (7.04%)	79 (39.11%)	< 0.01
Location
	Gingival	25 (35.21%)	40 (19.80%)	< 0.01
	Buccal	15 (21.13%)	22 (10.89%)
	Tongue	18 (25.35%)	79 (39.11%)
	Lip	5 (7.04%)	8 (3.96%)
	Palate	5 (7.04%)	7 (3.47%)
	Others	3 (4.23%)	46 (22.77%)
Notes: MPC: multiple primary cancers, SPC: single primary cancer, Others: oropharynx, floor of mouth, jawbone, retromolar.

There were 71 tumors from 34 MPCs patients. Regarding tumor location, tongue SCC was the most common location in the SPC group, accounting for 39.11% (79/202) of cases, while gingival SCC was the predominant location in MPCs patients (25/71; 35.21%). The incidence of lymph node metastasis was significantly lower in the MPCs group compared to the SPC group (p < 0.01). Furthermore, MPCs patients had a better initial tumor pathology grade compared to SPC patients (p < 0.01).

Although there was no significant difference in the age at the time of initial diagnosis during the early stage (within 42 months), the overall survival rate for MPCs initially appeared to be better than that for SPC (p = 0.874), but it subsequently became worse than SPC after 42 months (p = 0.002, Fig. 1a). Although the sample size of synchronous MPCs patients was restricted, the prognosis of synchronous MPCs patients was significantly worse than that of metachronous MPCs patients (p = 0.002) based on the Kaplan–Meier curve (Fig. 1b).

Copy Number Alteration Profiles of Different Tumors in the Same Patient

We collected a total of 71 tumor samples from 34 MPCs patients, 16 tumor samples from 8 recurrent patients, and 22 tumor samples from 11 lymph node metastasis patients for CNA sequencing profiles (Supplemental Table 1). The heatmap and frequency map revealed the presence of CNA events in all chromosomes (Fig. 2a, b). Notably, Chr7, Chr8, Chr9, Chr11 and Chr14 exhibited a high frequency of copy number gain events, while copy number losses were predominantly observed at a low frequency on Chr4 and Chr18. Additionally, Chr3 and Chr8 displayed breakpoints in all four groups. The hotspot regions described in MPCs patients were consistent with those previously reported in head and neck squamous cell carcinoma (HNSCC) ¹⁸, lung SCC¹⁹, and esophageal SCC ²⁰ and were also observed in recurrence and lymph node metastasis patients in our study.

Subsequently, we analyzed the CNA patterns of different tumors within the same patient. In the CNA profiles of recurrent patients and lymph node metastasis patients, highly similar CNA patterns were observed across all patients (Fig. 2a and Fig. 3a, b). For example, the CNA patterns of the tongue SCC (RP01-T2) that emerged 8 months after the resection of the first tumor (RP01-T1) in the recurrent patient RP01 were nearly identical (Fig. 3a). Similarly, the lymph node metastasis patient LNP03 exhibited common regions of CNA in Chr3, Chr5, Chr8, Chr10, Chr11, Chr20, Chr21, and Chr22 in both the primary tumor (LNP03-T1) and the lymph node tumor (LNP03-T2) (Fig. 3b).

In metachronous MPCs, we observed two scenarios in the CNA patterns. In 66.67% (20/30) of patients, tumors in different locations within the same patient displayed similar CNA regions. For instance, patient P24 was diagnosed with tumors in the left upper gingiva (P24-T1) and right buccal (P24-T2) with an interval of 88 months (Fig. 3c). The CNA results revealed common hotspots in Chr3, Chr8, and Chr20, as well as other distinct CNA events. Specifically, P24-T1 exhibited amplification in Chr2, Chr11, and Chr14, while the amplification region in P24-T2 was found in Chr5p. On the other hand, in 33.33% (10/30) of MPCs patients, the CNA profiles differed significantly between tumors in different locations within the same patient. For example, patient P15 presented with tumors in the buccal (P15-T1) and lip (P15-T2), with a 14-month interval between the two. P15-T1 exhibited CNA events in Chr3, Chr8, and Chr10, whereas the other tumor displayed different alterations in Chr12 (Fig. 3d). The degree of CNA similarity did not exhibit a consistent trend based on the temporal or spatial distance.

Similarly, in synchronous MPCs, two situations were observed. Three out of four patients demonstrated high similarity in their CNA patterns. For instance, patient P30 had tumors in the lower gingiva (P30-T1) and pharynx (P30-T2) simultaneously, and the two tumors shared CNA events on Chr1, Chr3, Chr5, Chr6, Chr7, Chr8, Chr11, Chr15, Chr17, Chr19, and Chr22 (Fig. 3e). However, patient P22, who had tongue SCC (P22-T1) and gingival SCC (P22-T2) as synchronous MPCs, exhibited mostly distinct CNA patterns (Fig. 3f). CNA events were observed in Chr3, Chr4, Chr5, Chr7 and Chr21 in P22-T1 but not in P22-T2.

Whole Exome Sequencing in MPCs Patients

WES was performed on individual tumors and normal tissues from four MPCs patients (P02, P12, P20, P34). The average number of reads per tumor was 67,870,702, with a ratio of high-quality clean reads ranging from 96.57–98.57%. Germline variants were removed by comparing the tumor data to the normal tissue data. Across all collected tumors, an average of 131,976 single nucleotide polymorphisms (SNPs) and 16,613 insertions and deletions (Indels) were observed per tumor (Supplemental Table 2).

The most common type of transition mutation in the tumors was C > T, observed in all samples (Supplemental Fig. 1). Regarding the tumor mutational burden (TMB), the mean TMB value for all lesions was 2.0 mutations per megabyte (MB), ranging from 0.94 to 3.94 mutations per MB (Supplemental Table 3). We focused on significantly mutated genes (SMGs) using MuSiC and identified a total of 97 SMGs (Supplemental Table 4). CASP8, an apoptosis-related gene, exhibited a mutation frequency of 75.00% (6/8), including three missense SNV(c.G700A:p.G234R, c.C773A:p.T258N, c.C773A:p.T258N) and one stopgain site mutations༈c.C1348T:p.Q450X༉ in three tumors (P12-T1, P20-T1 and P20-T2). The remaining samples (P02-T2, P34-T1 and P34-T2) showed non-frameshift deletions in amino acids 277–279 of the CASP8 gene. All CASP8 gene mutations were located in the same protein domain (Peptidase_C14) (Supplemental Fig. 2a). The top 2–4 genes with mutations were TP53 (63.00%), DNAH8 (50.00%), and GLI2 (50.00%). (Fig. 4a and Supplemental Table 4). Additionally, mutations in AHNAK2, GPR20, PCDHB10, CDKN2A, JMJD1C, AKAP13, and RRBP1 were also detected with a frequency of 37.50% (Supplemental Table 4). Although the sample size in our study was relatively small, we identified genes with high-frequency mutations that differ from those previously reported in OSCC²¹, suggesting the presence of unexplored genetic changes in MPCs patients that may contribute to disease development.

In addition to known OSCC driver genes (TP53 and CDKN2A) ²¹, our analysis revealed several genes not previously implicated in cancer. The HS3ST6 mutation was found in three samples from two patients, all occurring in the Sulfotransfer_1 structural domain (Supplemental Fig. 2b). The RFPL4A mutation was observed in two patients (three samples) in the SPRY domain, with a Polyphen score of 0.973, indicating harmful mutations (Supplemental Fig. 2c).

Pathway analysis using KEGG with the mutated genes in MPCs revealed the top three pathways as Pathways in cancer, Human cytomegalovirus infection, and Olfactory transduction (Fig. 4b and Supplemental Table 4).

Phylogenetic Tree Analysis in MPCs Patients

To gain insights into the genetic phylogeny of MPCs, we conducted a phylogenetic tree analysis based on SNVs and compared their CNA profiles (Fig. 5 and Supplemental Table 6). The branch length in the phylogenetic trees represented the number of mutations in the corresponding tumors, and the trunk mutations referred to the mutations shared by two tumors. Despite variations in the number of trunk mutations, ranging from 5 to 65, all four patients exhibited clear evidence of shared gene mutations.

Patient P34, who had synchronous MPCs, had the longest trunk length (n = 65). Furthermore, the CNA profiles of the two tumors in this patient showed a high degree of similarity, specifically in Chr3, Chr 5, Chr 7, Chr 8, Chr 11, Chr 14, Chr 17, and Chr 19. These findings indicate a close relationship between the two tumors in synchronous MPCs (Fig. 5).

In patients with metachronous MPCs, the length of trunk mutations was shorter compared to branch mutations (Supplemental Fig. 3). When considering both the CNA profiles and phylogenetic tree analysis of these three patients, the overall similarity was not significant. Trunk mutations ranged from 3–48%. Notably, we observed more unique changes between the two tumors in each individual.

In our study, we identified distinct clinical and pathological differences between MPCs and traditional OSCC. Interestingly, we observed a higher incidence of MPCs in females, while smoking and alcohol were not identified as risk factors. Furthermore, the affected sites in MPCs were predominantly the buccal mucosa and gingival mucosa, which differed from the most common site in traditional oral cancer, which is the tongue ²². These findings suggest that the risk factors for oral MPCs may differ from those of traditional oral cancer. Our study also showed a different gender ratio compared to a previous report on oral MPCs in Hong Kong, although the common sites of occurrence were consistent ²³.

The prognosis of MPCs compared to SPC remains controversial. Li et al. reported a poorer five-year survival rate for MPCs compared to SPC²⁴. In our study, we found that the prognosis of MPCs needs to be assessed separately. In the early stage (around less than 42 months), the prognosis of MPCs was slightly better than that of SPC, although not significantly. However, over time and with the impact of multiple cancer occurrences, the prognosis of MPCs became worse than that of SPC. This finding is consistent with the survival analysis conducted by Cai et al. based on the SEER database for MPCs ²⁵. We also observed that the prognosis of synchronous MPCs was significantly worse than that of metachronous MPCs, which aligns with reports on lung MPCs ²⁶.

We did not observe statistically significant differences in CNA events between different groups, including patients with recurrence, lymph node metastasis, and MPCs. Twenty years ago, some scholars proposed that the absence of 3p14 and 9p21 can serve as a simple diagnostic tool for oral MPCs ²⁷. However, SCC, including HNSCC¹⁸, lung SCC¹⁹, and esophageal SCC ²⁰, share common hotspot regions such as Chr 1, Chr 3, Chr 5, Chr 8, Chr 9, and Chr 11, which align with our CNA results(including MPCs, recurrence and lymph node metastasis patients). MPCs may not have distinctive CNA pattern that can be used to distinct it from SPC. The reasons for the diverse occurrence of aneuploidies CNA in tumors of MPC patients remain unclear, and the functional implications of CNA events in tumor patients are still to be explored ¹⁷.

Furthermore, in our attempt to identify potential pathogenic genes for oral MPCs, we found that in addition to commonly detected gene mutations such as TP53, CASP8, and MUC16, there were also relatively rare gene mutations compared to OSCC or head and neck squamous cell cancers. The SMGs identified in our study did not entirely match the results reported by Li et al. for oral MPCs ²⁴, except for TP53 and MUC16, which were also identified as highly frequent mutation genes ²⁴. This discrepancy may be due to the small sample size in both studies, including only 9 patients with a second primary cancer in that research and 8 samples from 4 patients in our study. Additionally, the functional significance of these rare mutation genes remains unclear, and there are currently no relevant research reports on their association with the occurrence of MPCs or even tumors.

The study of molecular clonality among different tumors in MPCs has been an ongoing area of research. Wang et al. analyzed the clonality of different lesions in lung MPCs using three methods: loss of heterozygosity, TP53 mutation screening analyses, and X-chromosome inactivation data²⁸. They found that 77% of lung MPCs were clonally related. Similarly, clonality was also observed in liver MPCs ²⁹. In a recent case report by Ba et al., common-driven genes were used to distinguish between lung MPCs and satellite nodules with lung metastasis³⁰. They concluded that different tumors in the same patient had distinct driver mutations, suggesting different molecular events driving the two tumors and influencing subsequent treatment approaches. Molecular methods have also been employed to differentiate recurrent cancer from MPCs in oral cancer. A study conducted in Taiwan utilized WES to sequence 15 patients with oral MPCs and identified driver genes and trunk mutations as distinguishing factors. The number of trunk mutations varied among MPCs cases, while recurrent patients exhibited completely duplicated mutated genes¹. However, the study did not differentiate between synchronous and metachronous MPCs, nor did it consider prognosis.

We did not observe a shared mutation gene in the trunk mutations among the four patients during the analysis of the phylogenetic tree. When comparing different tumors within the same patients we found that some metachronous cancer patients displayed distinct CNA patterns, while others exhibited varying degrees of CNA similarity. The similarity between synchronous MPCs was higher, and this pattern was more evident in patients with recurrence and lymph node metastasis, which aligns with the results reported by Scholes et al³¹. Additionally, both the CNA similarity analysis and phylogenetic tree analysis demonstrated consistent similarity among synchronous cancers. However, the results of CNA similarity analysis and phylogenetic tree analysis did not always align. For example, while CNA results categorized P02 as belonging to "some similar types," the phylogenetic tree analysis showed the lowest number of common gene mutations and no driven genes as common genes. There were also cases where the CNA results were completely inconsistent, but shared gene mutations were present (e.g., P12). It is possible that both CNA and trunk gene mutation methods can be used to evaluate the similarity of MPCs. On the other hand, this result also suggested the difficulty in identifying common driver genes in patients with oral multiple primary cancers, as patients exhibit significant individual variability. We have observed that various patients tend to possess distinct trunk genes, which could signify the critical involvement of this gene in the pathogenesis of individual, thus potentially emerging as prospective targets for personalized molecular therapies. Further investigation and attention are required to explore this disease comprehensively.

Gaining a deeper and more comprehensive comprehension of oral MPCs not only aids in distinguishing between patients with recurrence and metastasis from those with MPCs, but also opens up treatment possibilities for the latter group, ultimately reducing unnecessary utilization of medical resources. Presently, research on oral MPCs is constrained, encompassing both clinical pathology and molecular investigations, thereby posing challenges in employing a singular diagnostic tool for accurate detection. Comparable to other MPCs (e.g., lung), diverse molecular diagnostic criteria have been proposed, yet the consensus among experts remains rooted in the notion that distinguishing between a single primary and a metastatic tumor cannot solely rely on a single quantitative method⁹. The situation is akin to oral MPCs, where a comprehensive examination of various perspectives is required to elucidate the distinguishing characteristics of a singular primary tumor or MPCs.

This study has some limitations, including a small sample size for synchronous cancer and being a single-center study, which may have introduced bias into the final results. The underlying causes of oral MPCs are still unclear, as is the genetic relationship between the two tumors. Relying solely on individual molecular methods to diagnose the presence of MPCs is likely not feasible, and all evidence should be considered indicative. A comprehensive judgment based on clinical and pathological manifestations, as well as chromosomal changes and mutation genes, may be necessary.

Patient Cohort and Materials

This study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of Peking University Hospital of Stomatology (PKUSSIRB-201949116). A retrospective search for patients with MPCs was conducted at Peking University Hospital of Stomatology from 2000 to 2021. The focus of this study was on multiple primary OSCCs. We selected patients with OSCC that occurred in different locations, defined according to the criteria determined by Warren and Gates in 1932. The tumor locations were coded based on the anatomic location using the International Classification of Diseases, 10th Revision (ICD-10). The interval between MPCs can be divided into simultaneous cancer (interval ≤ 6 months) and metachronous cancer (interval > 6 months) by IACR/IARC system.

Simultaneously, OSCC patients diagnosed with recurrence or lymph node metastasis were also included. The diagnostic criteria for recurrence followed the Odense Birmingham definition ³², and lymph node metastasis was determined based on lymph node dissection during primary cancer surgery. Tumor size and lymph node positivity were coded according to the latest UICC TNM classification³³. All patients included in the study had formalin-fixed and paraffin-embedded (FFPE) samples or frozen tissue available for analysis.

Additionally, clinical-pathological data of patients with SPC who visited Peking University Hospital of Stomatology in 2017 and had six-year follow-up information were collected.

Sample Selection and Copy Number Alteration Sequencing

FFPE samples from different locations within the oral cavity (lymph node samples for metastasis patients) were collected for CNA sequencing, following previous reports ³⁴. Briefly, a 10 µm section was prepared using REM710 (Yamato, Japan) and then subjected to UV laser cutting using LMD7 (Leica) to capture tissues, ensuring a cell count between 300–600 per sample. Tissues were lysed, and all libraries were sequenced using an Illumina HiSeq 4000 sequencer with PE150 sequencing strategy. The 2 × 150 paired-end reads were trimmed using Cutadapt (version 2.10) to remove adapters and aligned to the human reference genome (hg19) using the Bowtie2 aligner (version 2.2.9). Non-overlapping dynamic bins with 1Mb resolution were generated across the genome. The bin counts were obtained, and CNA calling was performed using the circular binary segmentation (CBS) algorithm. The sequencing depth for each sample was approximately 0.3 Gb (0.1×). The major parameters used to filter out low-quality samples were median absolute pairwise difference (MAPD) and the number of mapping reads (samples with MAPD < 0.3 and reads > 100,000 were considered of qualified quality).

Whole-Exome Sequencing and Data Analysis

Fresh tissue samples stored at -80°C were used for DNA extraction using the QIAamp Blood and Tissue DNA Kit (QIAamp, Germany). WES was performed using the Agilent SureSelect Human All Exon V6 kit (Agilent, USA) to capture and enrich exome sequences. High-throughput sequencing was conducted on Illumina platforms with PE150 strategy at Novogene Bioinformatics Technology Co., Ltd (Beijing, China).

Total read numbers, raw data, error rates, and the percentage of reads with Q30 scores (the percent of bases with Phred-scaled quality scores greater than 30) were calculated and summarized. The filtered reads were mapped to the reference genome (b37) using Burrows-Wheeler Aligner (BWA) software ³⁵ and Samblaster³⁶ to generate a BAM file. Germline single nucleotide polymorphisms (SNPs) and InDels were called using SAMtools ³⁷ with the following filter parameters: QUAL ≥ 20, DV ≥ 4, MQ ≥ 30. SNV mutations were detected using MuTect³⁸, and somatic InDels were identified by Strelka³⁹. Variant annotation was performed using ANNOVAR⁴⁰. MuSiC ⁴¹ and the Kyoto Encyclopedia of Genes and Genomes (KEGG)⁴² were employed for selecting SMGs and pathway annotation, respectively. Phylogenetic trees were constructed using Phylip-3.695 to compare non-synonymous gene mutations. Select variants were validated with Sanger sequencing (Supplemental table 7).

Statistical Methods

Statistical analysis was conducted using IBM SPSS Statistics 25.0 (IBM Corp., Armonk, NY, USA) and R 4.1.1. Polyphen-2, a tool for predicting the deleterious effects of gene mutations, was employed. A higher Polyphen-2 score indicates a greater level of harm (http://genetics.bwh.harvard.edu/pph2/index.shtml). Clinical data, including age, gender, locations of oral cancer, smoking history, and drinking history, were compared between MPCs and SPC groups using the Mann-Whitney U test, Chi-square test, or Fisher's exact test, as appropriate. The survival rate of MPCs and SPC patients was calculated using the Kaplan-Meier method, and we compared the survival curves using a log-rank test to test differences in survival probabilities across group. Statistical significance was defined as a p-value less than 0.05.

Acknowledgements

This work was supported by the National Nature Science Foundation of China (China, grant numbers 81671006, 81300894), CAMS Innovation Fund for Medical Sciences (China, grant number 2019-I2M-5-038), National Clinical Key Discipline Construction Project (China, PKUSSNKP-202102).

Conflict of interests

The author(s) declare that they have no conflict of interest.

Contributions

T.L., H.Z., and X.Z. designed the study. X.Z., X.C., J.Z., and F.J. collected and analyzed the data. X.Z. and X.C., and X.L. completed the experiment. X.Z., X.C., F.J., X.L., J.Z., drafted the manuscript. H.Z. and T. L oversaw statistical analyses, interpreted the results, and reviewed the manuscript. All authors have approved the final report for publication.

Liu, T.-Y. et al. Mutation Analysis of Second Primary Tumors in Oral Cancer in Taiwanese Patients through Next-Generation Sequencing. Diagnostics 12, 951 (2022).
Zecha, J. A. E. M. et al. Low-level laser therapy/photobiomodulation in the management of side effects of chemoradiation therapy in head and neck cancer: part 2: proposed applications and treatment protocols. Support. Care Cancer Off. J. Multinatl. Assoc. Support. Care Cancer 24, 2793–2805 (2016).
Shield, K. D. et al. The global incidence of lip, oral cavity, and pharyngeal cancers by subsite in 2012. CA. Cancer J. Clin. 67, 51–64 (2017).
Kyrgidis, A. et al. Clinical, histological and demographic predictors for recurrence and second primary tumours of head and neck basal cell carcinoma. A 1062 patient-cohort study from a tertiary cancer referral hospital. Eur. J. Dermatol. 20, 276–282 (2010).
Warren S & Gates O. Multiple primary malignant tumors. a survey of the literature and a statistical study. Am. J. Cancer (1932).
Thakur, M. K. et al. Risk of Second Lung Cancer in Patients with Previously Treated Lung Cancer: Analysis of Surveillance, Epidemiology, and End Results (SEER) Data. J. Thorac. Oncol. Off. Publ. Int. Assoc. Study Lung Cancer 13, 46–53 (2018).
International Association of Cancer Registries. International rules for multiple primary cancers. Asian Pac. J. Cancer Prev. APJCP 6, 104–106 (2005).
Braakhuis, B. J. M. et al. Second primary tumors and field cancerization in oral and oropharyngeal cancer: Molecular techniques provide new insights and definitions. Head Neck 24, 198–206 (2002).
Detterbeck, F. C. et al. The IASLC Lung Cancer Staging Project: Background Data and Proposed Criteria to Distinguish Separate Primary Lung Cancers from Metastatic Foci in Patients with Two Lung Tumors in the Forthcoming Eighth Edition of the TNM Classification for Lung Cancer. J. Thorac. Oncol. Off. Publ. Int. Assoc. Study Lung Cancer 11, 651–665 (2016).
Slaughter, D. P., Southwick, H. W. & Smejkal, W. Field cancerization in oral stratified squamous epithelium; clinical implications of multicentric origin. Cancer 6, 963–968 (1953).
Braakhuis, B. J. M., Tabor, M. P., Kummer, J. A., Leemans, C. R. & Brakenhoff, R. H. A genetic explanation of Slaughter’s concept of field cancerization: evidence and clinical implications. Cancer Res. 63, 1727–1730 (2003).
Li, F. et al. p73 G4C14-to-A4T14 polymorphism and risk of second primary malignancy after index squamous cell carcinoma of head and neck. Int. J. Cancer 125, 2660–2665 (2009).
Lei, D. et al. FAS and FASLG Genetic Variants and Risk for Second Primary Malignancy in Patients with Squamous Cell Carcinoma of the Head and Neck. Cancer Epidemiol. Biomarkers Prev. 19, 1484–1491 (2010).
Wang, Z. et al. Genetic variants of p27 and p21 as predictors for risk of second primary malignancy in patients with index squamous cell carcinoma of head and neck. Mol. Cancer 11, 17 (2012).
Jin, L. et al. Genetic variants in p53-related genes confer susceptibility to second primary malignancy in patients with index squamous cell carcinoma of head and neck. Carcinogenesis 34, 1551–1557 (2013).
Rettori, M. M. et al. TIMP3 and CCNA1 hypermethylation in HNSCC is associated with an increased incidence of second primary tumors. J. Transl. Med. 11, 316 (2013).
Girish, V. et al. Oncogene-like addiction to aneuploidy in human cancers. Science eadg4521 (2023) doi:10.1126/science.adg4521.
Cancer Genome Atlas Network. Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature 517, 576–582 (2015).
Martinez, V. D. et al. Arsenic-related DNA copy-number alterations in lung squamous cell carcinomas. Br. J. Cancer 103, 1277–1283 (2010).
Chang, J. et al. Genomic analysis of oesophageal squamous-cell carcinoma identifies alcohol drinking-related mutation signature and genomic alterations. Nat. Commun. 8, 15290 (2017).
Stransky, N. et al. The Mutational Landscape of Head and Neck Squamous Cell Carcinoma. Science 333, 1157–1160 (2011).
López de Cicco, R., Watson, J. C., Bassi, D. E., Litwin, S. & Klein-Szanto, A. J. Simultaneous expression of furin and vascular endothelial growth factor in human oral tongue squamous cell carcinoma progression. Clin. Cancer Res. Off. J. Am. Assoc. Cancer Res. 10, 4480–4488 (2004).
Choi, S. & Thomson, P. Multiple oral cancer development—Clinico‐pathological features in the Hong Kong population. J. Oral Pathol. Med. 49, 145–149 (2020).
Li, K. et al. Preliminary study on the molecular features of mutation in multiple primary oral cancer by whole exome sequencing. Front. Oncol. 12, 971546 (2022).
Cai, X. et al. Clinical and prognostic features of multiple primary cancers with oral squamous cell carcinoma. Arch. Oral Biol. 149, 105661 (2023).
Adebonojo, S. A., Moritz, D. M. & Danby, C. A. The results of modern surgical therapy for multiple primary lung cancers. Chest 112, 693–701 (1997).
Rosin, M. P. et al. 3p14 and 9p21 loss is a simple tool for predicting second oral malignancy at previously treated oral cancer sites. Cancer Res. 62, 6447–6450 (2002).
Wang, X. et al. Evidence for Common Clonal Origin of Multifocal Lung Cancers. JNCI J. Natl. Cancer Inst. 101, 560–570 (2009).
Hodges, K. B. et al. Clonal origin of multifocal hepatocellular carcinoma. Cancer 116, 4078–4085 (2010).
Ba, Y. et al. Case report: targeted sequencing improves the diagnosis of multiple synchronous lung cancers. Transl. Lung Cancer Res. 12, 933–939 (2023).
Scholes, A. G. et al. Synchronous oral carcinomas: independent or common clonal origin? Cancer Res. 58, 2003–2006 (1998).
Rohde, M. et al. Definition of locally recurrent head and neck squamous cell carcinoma: a systematic review and proposal for the Odense-Birmingham definition. Eur. Arch. Oto-Rhino-Laryngol. Off. J. Eur. Fed. Oto-Rhino-Laryngol. Soc. EUFOS Affil. Ger. Soc. Oto-Rhino-Laryngol. - Head Neck Surg. 277, 1593–1599 (2020).
Huang, S. H. & O’Sullivan, B. Overview of the 8th Edition TNM Classification for Head and Neck Cancer. Curr. Treat. Options Oncol. 18, 40 (2017).
Li, X. et al. Improvement in the risk assessment of oral leukoplakia through morphology-related copy number analysis. Sci. China Life Sci. 64, 1379–1391 (2021).
Li, H. & Durbin, R. Fast and accurate long-read alignment with Burrows–Wheeler transform. Bioinformatics 26, 589–595 (2010).
Faust, G. G. & Hall, I. M. SAMBLASTER : fast duplicate marking and structural variant read extraction. Bioinformatics 30, 2503–2505 (2014).
Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
Cibulskis, K. et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat. Biotechnol. 31, 213–219 (2013).
Saunders, C. T. et al. Strelka: accurate somatic small-variant calling from sequenced tumor–normal sample pairs. Bioinformatics 28, 1811–1817 (2012).
Wang, K., Li, M. & Hakonarson, H. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res. 38, e164–e164 (2010).
Dees, N. D. et al. MuSiC: Identifying mutational significance in cancer genomes. Genome Res. 22, 1589–1598 (2012).
Kanehisa, M. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27–30 (2000).

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You are reading this latest preprint version

Genomic Alterations in Oral Multiple Primary Cancers

Status:

Version 1

Abstract

Figures

Introduction

Result

Clinicopathological Differences between MPCs and SPCs

Copy Number Alteration Profiles of Different Tumors in the Same Patient

Whole Exome Sequencing in MPCs Patients

Phylogenetic Tree Analysis in MPCs Patients

Discussion

Methods and material

Patient Cohort and Materials

Sample Selection and Copy Number Alteration Sequencing

Whole-Exome Sequencing and Data Analysis

Statistical Methods

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1