Aristolochic acid, an herbal compound found in many traditional medicines, had been previously linked to kidney failure, as well as cancers of the urinary tract. Because of these known toxicities, herbs containing this compound have been restricted or banned in some countries, but it is still available on the internet and in alternate formulations. By analyzing numerous samples from Taiwan and other countries in Asia and elsewhere, Ng et al. demonstrated the effects of aristolochic acid in hepatocellular carcinoma, a much more common tumor type. The authors showed that the use of this drug remains widespread in Asia and particularly in Taiwan, and that it appears to increase the risk of multiple different cancer types.

Many traditional pharmacopeias include Aristolochia and related plants, which contain nephrotoxins and mutagens in the form of aristolochic acids and similar compounds (collectively, AA). AA is implicated in multiple cancer types, sometimes with very high mutational burdens, especially in upper tract urothelial cancers (UTUCs). AA-associated kidney failure and UTUCs are prevalent in Taiwan, but AA’s role in hepatocellular carcinomas (HCCs) there remains unexplored. Therefore, we sequenced the whole exomes of 98 HCCs from two hospitals in Taiwan and found that 78% showed the distinctive mutational signature of AA exposure, accounting for most of the nonsilent mutations in known cancer driver genes. We then searched for the AA signature in 1400 HCCs from diverse geographic regions. Consistent with exposure through known herbal medicines, 47% of Chinese HCCs showed the signature, albeit with lower mutation loads than in Taiwan. In addition, 29% of HCCs from Southeast Asia showed the signature. The AA signature was also detected in 13 and 2.7% of HCCs from Korea and Japan as well as in 4.8 and 1.7% of HCCs from North America and Europe, respectively, excluding one U.S. hospital where 22% of 87 “Asian” HCCs had the signature. Thus, AA exposure is geographically widespread. Asia, especially Taiwan, appears to be much more extensively affected, which is consistent with other evidence of patterns of AA exposure. We propose that additional measures aimed at primary prevention through avoidance of AA exposure and investigation of possible approaches to secondary prevention are warranted.

Inference of high rates of AA exposure in Taiwan is based on the following evidence: (i) prescription records indicating about one-third of the population exposed to AA ( 28 ), (ii) high rates of UTUCs and co-association of kidney failure and UTUCs ( 40 , 41 ), (iii) presence of AA-DNA adducts associated with UTUCs and RCCs ( 26 , 34 ), and (iv) presence of the AA mutational signature in UTUCs, BCs, and RCCs from Taiwan ( 29 – 31 , 34 ). However, despite the high amount of AA exposure in Taiwan and reports of the AA mutational signature in HCCs from China and other areas, AA exposure in Taiwan HCCs remains unexplored.

In the early 1990s, inadvertent treatment with AA-containing herbs at a Belgian weight loss clinic caused kidney failure in ~100 women ( 25 ), many of whom later developed bladder and upper tract urothelial carcinomas (UTUCs) ( 9 ). Subsequently, additional reports of kidney failure and urothelial cancers due to AA poisoning appeared, and it emerged that AA was also responsible for Balkan endemic nephropathy ( 9 ). Taiwan also emerged as a hot spot for AA exposure based on prescription records and high rates of kidney failure and UTUCs, which are likely to be partly due to AA exposure ( 26 – 30 ). More recently, mutational signature analysis and other lines of evidence have suggested that AA mutagenesis may be widespread in terms of both geography and types of cancer affected ( 10 ). In particular, after we and others described a distinctive mutational signature of AA exposure in the genomes of UTUCs from Taiwan ( 29 , 30 ), this signature was also found in bladder carcinomas (BCs) from Taiwan and other regions ( 31 ), renal cell carcinomas (RCCs) from Taiwan and the Balkans ( 32 – 34 ), intrahepatic bile duct carcinomas from China ( 35 ), bile duct carcinomas from Singapore ( 36 ), and hepatocellular carcinomas (HCCs) from China, Vietnam, and other Southeast Asian countries ( 29 , 37 – 39 ).

Mutational signature analysis has been particularly helpful in illuminating the epidemiology of tumors associated with aristolochic acids and their derivatives (collectively, AA). Among these compounds, the in vitro toxicity and mutagenicity of aristolochic acids and aristolactams have been most intensively studied ( 6 – 8 ). AAs include potent mutagens and nephrotoxins present in plants in the genera Aristolochia and Asarum, as well as related plants ( 6 , 7 ). Many of these plants are used as herbal medicines ( 9 – 18 ). AA mutagenesis is thought to stem from the formation of bulky adducts on purines ( 19 – 21 ). For reasons that are imperfectly understood, but possibly related to better repair of AA-guanine adducts, more accurate translesion synthesis across AA-guanine adducts, or both, AA induces adenine-to-thymine (A>T) mutations almost exclusively ( 9 , 20 , 22 – 24 ).

Mutational signature analysis provides a molecular epidemiological tool for detecting environmental exposures that cause cancers ( 1 – 5 ). This has important implications for public health by providing evidence to substantiate causal links between exposures and tumors, providing opportunities for primary and secondary prevention. Mutational signature analysis may also affect clinical oncology in situations where identifiable mutagenic exposures suggest specific cancer risks or preferred treatments.

RESULTS

Overview of somatic changes in 98 HCCs from Taiwan To investigate the possible presence of the AA mutational signature in HCCs from Taiwan, we sequenced the exomes of 98 HCCs and matched nonmalignant tissues from two hospitals (table S1). Tumor tissue was obtained from nonconsecutive patients, and inclusion in this study was solely based on the availability of adequate DNA. Tumors were not selected based on suspicion of AA exposure. We sequenced whole exomes, with a mean of 95% targeted tumor bases with ≥30× coverage (table S2). We detected a total of 26,805 somatic single-base substitution (SBS) mutations across the HCCs (median, 167 SBS per tumor; interquartile range, 103 to 316), with an estimated false discovery rate (FDR) of 1.9% (tables S3 and S4). We detected a total of 648 short insertions or deletions (indels; median, 6 indels per tumor; interquartile range, 3 to 9), with an estimated FDR of 3.2% (tables S3 and S5). In total, 10,174 genes harbored nonsilent SBS mutations (table S4). Driver analysis with MutSigCV (42) and 20/20+ (43) identified 16 significantly mutated genes (tables S6 to S8). The most commonly mutated genes—TP53, CTNNB1, ALB, and AXIN1—were also the most commonly mutated in the recent TCGA (The Cancer Genome Atlas) report (37), but the proportions of tumors with mutations in these genes were higher in the Taiwan HCCs (table S6). Among these genes, it has been proposed that ALB inactivation may promote cancer development by “diverting energy into cancer-relevant metabolic pathways” (37, 44). An additional gene identified by this analysis was IRF2, which was previously reported to act as a tumor suppressor in HCC (45). Of the other genes, two have not been identified as likely drivers in previous genome- or exome-wide resequencing of HCCs, and other evidence of their roles in cancer is absent or very limited, suggesting a lack of functional roles in HCC (table S6). Previously observed genomically amplified oncogenes and deleted tumor suppressors were also amplified or deleted in the Taiwan HCCs (fig. S1). These genes included the amplified oncogene CCND1 and the deleted tumor suppressor RB1 (37, 39, 46–49).

High rates of the AA mutational signature in Taiwan HCCs The mutational spectra of most of the HCCs from Taiwan showed marked evidence of AA exposure, in the form of high proportions of A:T>T:A mutations in the trinucleotide contexts characteristic of AA-exposed tumors and cell lines (Fig. 1, A to D, and fig. S2) (29–31), although some HCCs did not show this evidence (Fig. 1E and fig. S2). The trinucleotide contexts characteristic of AA exposure included a prominent peak at 5′-CTG-3′ (5′-CAG-3′ on the complementary strand). There was also a notable excess of A>T mutations on the nontranscribed strands of genes, which is characteristic of AA-induced mutations in other tumor types and in cell lines (29–35). Principal components analysis clustered the majority of the Taiwan HCCs away from other HCCs and with previously reported AA-associated UTUCs (29, 30) and BCs (31) and with AA-exposed cell lines (Fig. 1F) (29). Fig. 1. Evidence of AA exposure in Taiwan HCCs. (A and B) Sample exome spectra of individual AA-exposed UTUCs (A) and BCs (B) from Taiwan. (C and D) Sample exome spectra of individual Taiwan HCCs with high (C) and moderate (D) levels of the AA signature. (E) Sample Taiwan HCC without AA signature. In the major plots in (A) to (E), each bar indicates the proportion of mutations in a particular trinucleotide context. In the AA signature (A to D), the overwhelming majority of mutations are T:A>A:T. By convention, mutations are shown as T>A (for example) rather than A>T, although AA mutations are physical consequences of adducts on adenines that cause A>T mutations (9, 20, 22–24). In tumors strongly mutagenized by AA, the most prominent peak is at CTG>CAG (CAG>CTG on the complementary strand), indicated in (A), often with additional prominent peaks at CTA>CAA and ATG>AAG. Small plots at right in (A) to (E) show transcription strand bias. Mut count, mutation count. (F) Mutation spectra–based principal components analysis of HCCs from Taiwan, China (52), and Japan (53), plus AA-exposed UTUCs (29) and BCs (31) and an AA-exposed cell line (29). The most distinguishable features are the T>A mutations induced by AA, which are reflected in PC1. PC1 explains 35% of the variance, and PC2 explains 5.5%. To systematically assess the extent of AA exposure across the 98 HCCs, we developed the mSigAct (mutational signature activity) software. mSigAct provides a signature presence test to infer whether observed mutation spectra are better explained with a contribution from the AA mutational signature [Catalogue of Somatic Mutations in Cancer (COSMIC) signature 22] than without. We developed mSigAct because, to our knowledge, current approaches, most of which are based on nonnegative matrix factorization (NMF), do not support statistical inference of the presence or absence of a signature (3, 4, 50, 51). Briefly, the mSigAct test starts by generating optimal coefficients for reconstruction of the observed spectrum using the mutational signatures previously detected in HCCs. The test first does this without the AA signature (null hypothesis) and then with the AA signature (alternative hypothesis). The test then carries out a standard likelihood ratio test on these two hypotheses. Supplementary Materials and Methods and codes S1 and S2 provide details on the test, its evaluation on synthetic data, and the code. mSigAct revealed strong evidence of AA exposure in 76 of the 98 HCCs (78% with FDR < 0.05; Fig. 2, Table 1, and table S9). Among tumors with the AA signature, there was a median of 2.26 AA signature mutations/Mb (mean, 4.94 AA signature mutations/Mb). Fig. 2. Mutational signature exposures in Taiwan HCCs and summary of AA signature mutations. (A) Estimated numbers of mutations due to each mutational signature in each HCC. AA is COSMIC signature 22. W6 is from (53). COSMIC signatures 4 and 24 reflect known exogenous risk factors for HCC: tobacco smoking and aflatoxin exposure, respectively. MMR, mismatch repair. (B) Proportions of tumors with the AA signature in various groups of HCCs. “Southeast Asia” indicates Southeast Asia excluding Vietnam; “Mayo Clinic” denotes a group of HCCs from patients treated at that clinic for whom there was no country information and who we speculate may have traveled from Asia for treatment; “No information” denotes TCGA HCCs from biobanks for which there is no information on geographic origin. (C) Densities and counts of AA signature mutations among tumors with the AA signature. Each mutation is associated with a weighted assignment of the probability that it was caused by the AA signature (see Materials and Methods). The weighted count of AA signature mutations is the sum of these probabilities across all mutations in the tumors. The geographical regions indicated at the right of (B) also apply to (C). Table 1. Summary of AA signature mutations in HCCs. View this table: As a further check on the mSigAct signature presence test, we also analyzed the 98 Taiwan HCCs with the NMF procedure in (3, 4) (code S1). The signature extracted by NMF had a Pearson correlation coefficient of 0.997 and a cosine similarity of 0.997 with the AA signature (COSMIC signature 22; fig. S3 and table S10). We also used NMF to detect the presence or absence of the AA signature and compared the results for this to those from the mSigAct signature presence test. The two procedures were concordant for 90 tumors (code S1). NMF identified eight putatively AA-exposed HCCs that mSigAct did not identify (T18, T41, T50, T53, T57, T61, T68, and T92; fig. S2). Thus, the mSigAct signature presence test was more conservative; the tumors identified by NMF but not mSigAct had very low numbers of A>T mutations (all but one ≤15) in backgrounds of relatively high numbers of other mutations, making it difficult to be confident of AA exposure (code S1). We would propose that this is the desired characteristic, that is, it is preferable to err on the side of undercalling rather than overcalling the presence of the AA signature. Furthermore, testing on synthetic data also indicated that the mSigAct signature presence test had better sensitivity and specificity (Supplementary Materials and Methods and code S2). We examined associations between the extent of exposure to the AA signature and multiple clinical and epidemiological variables, namely, hospital, cirrhosis status, hepatitis B carrier status, hepatitis C carrier status, status as carrier of either hepatitis virus, diagnosis before or after the medicinal use of some AA-containing plants was banned in Taiwan in 2003, gender, date of diagnosis, and age at diagnosis (fig. S4). Of these, without correction for multiple hypothesis testing, AA exposure differed significantly by gender and age at diagnosis. There was a weak association of increased AA exposure with age (Spearman’s rho = 0.28, P = 0.008). In addition, AA mutation numbers were higher in females than in males (median, 176 versus 55 AA signature mutations per HCC; P = 0.015 by two-sided Wilcoxon rank sum test). After considering multiple hypothesis testing, the Benjamini-Hochberg FDRs for both gender and age were 0.065. Although AA mutation numbers were not statistically higher in women than in men, we note other evidence of more exposure to AA-containing herbs among women: In Taiwan before the ban, exposures were 31.6 person-years per 1000 for women compared to 25.9 for men (28). We also note that, because only 10 HCCs were hepatitis-negative, these data did not offer an opportunity to investigate interactions between hepatitis and AA exposure.

The AA mutational signature in HCCs from other regions Given the high prevalence of the AA signature in Taiwan HCCs, we examined publicly available data comprising 1400 HCCs (Table 1). These included data from China, Japan, Korea, and several countries in Southeast Asia (37–39, 46–48, 52, 53), as well as data from North America and Europe (37, 49) as negative controls with likely rare AA exposure. We detected the AA signature in 42 of 89 HCCs (47%) from China (Figs. 2 to 4; Table 1; fig. S5, A and B; and table S11). Among the HCCs from earlier studies (47, 52), the mSigAct signature presence test detected many more affected HCCs than we were able to identify previously (29). Overall, however, AA signature mutation burdens were lower in China (median, 0.29 AA signature mutations/Mb) than in Taiwan (median, 2.26 AA signature mutations/Mb). Fig. 3. Sample spectra of HCCs with the AA signature. Display conventions are the same as in Fig. 1. Fig. 4. Global distribution of mutagenesis associated with aristolochic acid and derivatives in HCCs. The pie chart labeled “Southeast Asia” includes both Vietnam and the other Southeast Asian HCCs. Pie chart areas are proportional to the number of HCCs in the given group. We detected the AA signature in five of nine HCCs from various countries in Southeast Asia other than Vietnam (56%; fig. S5, C and D) (39). Among the HCCs with the AA signature, the median mutation burden was high (2.9 AA signature mutations/Mb). We also detected the signature in 5 of 26 HCCs from Vietnam (19%) (37), with a high median mutation burden of 3.4 AA signature mutations/Mb (fig. S5E). We also detected the AA signature in lower proportions of the HCCs from Korea and Japan (Table 1; Figs. 2, B and C, and 3; and fig. S5, F to H). We analyzed TCGA data (37) from areas other than Vietnam in several subgroups (fig. S5I). In the largest subgroup, North America, we detected AA signature mutations in 10 of 209 HCCs (5%; Table 1 and fig. S5J). Among HCCs from North America, the proportion with the AA signature from “Asian” patients (2/20) was not significantly different from non-Asian patients (8/189). We also detected AA signature mutations in 4 of 230 HCCs from Europe (1.7%; fig. S5K). This low proportion is consistent with the rarity of reports of AA exposure in Europe outside of the Balkans and the Belgian poisoning incident in the 1990s (9, 25, 32, 33). Furthermore, the median AA mutation burden was low (0.35 AA signature mutations/Mb), although one HCC with likely DNA mismatch repair deficiency had many more mutations. Within the TCGA data (37), there were 89 HCCs from the Mayo Clinic for which the “Country” field had no data, and almost all of these (87) had “Ethnicity” listed as Asian. Among these, 19 (21%) had the AA signature (fig. S5L). Given the high prevalence of the signature and relatively high numbers of AA signature mutations in these HCCs (median, 1.3 AA signature mutations/Mb), we speculate that some of these patients may have traveled from Asia for treatment. In addition, there were 30 HCCs from biobanks for which no Country information was available. Of these, 20 were listed as Asian, and 5 (25%) of these had the AA signature, whereas none of the non-Asian HCCs had the AA signature (fig. S5M). Finally, one of five HCCs from Brazil with non-Asian ethnicity (20%) showed the AA signature (fig. S5N). The effects of the AA signature were especially prominent in Taiwan: A higher proportion of HCCs from Taiwan showed the AA signature than in any group other than the nine HCCs from Southeast Asia (not including the HCCs from Vietnam; Table 1). Nevertheless, this analysis of publicly available data showed widespread AA exposure in East and Southeast Asia and in self-identified Asians elsewhere.

AA signature mutations in known cancer drivers Our initial analyses with MutSigCV and 20/20+ did not reveal any strong possibilities for previously unknown driver genes in the Taiwan HCCs, but many genes listed in the Cancer Gene Census as known cancer drivers (table S12) were affected by nonsilent mutations ascribed to the AA signature (54). Across all Taiwan HCCs, the AA signature accounted for 59% (299 of 505) of nonsilent mutations in known driver genes (table S9). Among the Taiwan HCCs, 57 had a nonsilent AA mutation in ≥1 known driver (Fig. 2C, Table 1, and table S9). Among HCCs with the AA signature, two genes, TP53 and LRP1B, were mutated frequently by both A>T and by non-A>T mutations (39 and 27 total nonsilent mutations, respectively, of which 48 and 63% were AA signature mutations; table S13). Recurrent mutations in LRP1B could be due to its large size (4599 amino acids; UniProt accession code Q9NZR2). It was not identified as a driver in our MutSigCV and 20/20+ analysis, and experimental evidence that it can function as a tumor suppressor is limited (55, 56). Several known tumor suppressors harbored predominantly AA signature mutations (table S13). Three of these are WNT-related tumor suppressors: AXIN1, AXIN2, and APC. Three others—ARID1A, ARIDB, and SETD2—are involved in chromatin remodeling, as is the oncogene KMT2A. Tumors with the AA signature from regions other than Taiwan also had driver genes harboring nonsilent AA signature mutations (Table 1, Fig. 2C, and table S13). For example, 19 of the 29 AA-affected HCCs from Korea and all 5 of the AA-affected HCCs from Vietnam had AA signature mutations in known driver genes. Clonality analysis of the Taiwan HCCs that had the AA signature suggested that AA mutations are predominantly early events, which is consistent with exposure before carcinogenesis (fig. S6). However, some AA signature mutations were subclonal, indicating that AA-associated mutagenesis, and presumably AA exposure, continued during tumor development and growth. Phylogenic analysis based on multisector sequencing of HCCs from China in (38) showed that most AA mutations were truncal (found in all regions of the tumors), but some were subclonal, suggesting additional exposure to AA after initiation of carcinogenesis. A reanalysis of HCCs treated in Singapore showed a similar pattern of predominantly truncal AA signature mutations in four of the five AA-affected tumors (table S14) (39).